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Sample records for dynamic pharmacophore model

  1. Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

    SciTech Connect

    Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen; Bushman, Frederic; Jorgensen, William L.; Lins, Roberto; Briggs, James; Mccammon, Andy

    2000-05-11

    We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.

  2. Developing a dynamic pharmacophore model for HIV-1 integrase.

    PubMed

    Carlson, H A; Masukawa, K M; Rubins, K; Bushman, F D; Jorgensen, W L; Lins, R D; Briggs, J M; McCammon, J A

    2000-06-01

    We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of "dynamic" pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a "static" pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors. PMID:10841789

  3. Pharmacophore modeling, in silico screening, molecular docking and molecular dynamics approaches for potential alpha-delta bungarotoxin-4 inhibitors discovery

    PubMed Central

    Kumar, R. Barani; Suresh, M. Xavier; Priya, B. Shanmuga

    2015-01-01

    Background: The alpha-delta bungartoxin-4 (α-δ-Bgt-4) is a potent neurotoxin produced by highly venomous snake species, Bungarus caeruleus, mainly targeting neuronal acetylcholine receptors (nAchRs) and producing adverse biological malfunctions leading to respiratory paralysis and mortality. Objective: In this study, we predicted the three-dimensional structure of α-δ-Bgt-4 using homology modeling and investigated the conformational changes and the key residues responsible for nAchRs inhibiting activity. Materials and Methods: From the selected plants, which are traditionally used for snake bites, the active compounds are taken and performed molecular interaction studies and also used for modern techniques like pharmacophore modeling and mapping and absorption, distribution, metabolism, elimination and toxicity analysis which may increase the possibility of success. Results: Moreover, 100's of drug-like compounds were retrieved and analyzed through computational virtual screening and allowed for pharmacokinetic profiling, molecular docking and dynamics simulation. Conclusion: Finally the top five drug-like compounds having competing level of inhibition toward α-δ-Bgt-4 toxin were suggested based on their interaction with α-δ-Bgt-4 toxin. PMID:26109766

  4. Exploration of Virtual Candidates for Human HMG-CoA Reductase Inhibitors Using Pharmacophore Modeling and Molecular Dynamics Simulations

    PubMed Central

    Sakkiah, Sugunadevi; Park, Chanin; John, Shalini; Lee, Keun Woo

    2013-01-01

    3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors. PMID:24386216

  5. Pharmacophore-Map-Pick: A Method to Generate Pharmacophore Models for All Human GPCRs.

    PubMed

    Dai, Shao-Xing; Li, Gong-Hua; Gao, Yue-Dong; Huang, Jing-Fei

    2016-02-01

    GPCR-based drug discovery is hindered by a lack of effective screening methods for most GPCRs that have neither ligands nor high-quality structures. With the aim to identify lead molecules for these GPCRs, we developed a new method called Pharmacophore-Map-Pick to generate pharmacophore models for all human GPCRs. The model of ADRB2 generated using this method not only predicts the binding mode of ADRB2-ligands correctly but also performs well in virtual screening. Findings also demonstrate that this method is powerful for generating high-quality pharmacophore models. The average enrichment for the pharmacophore models of the 15 targets in different GPCR families reached 15-fold at 0.5 % false-positive rate. Therefore, the pharmacophore models can be applied in virtual screening directly with no requirement for any ligand information or shape constraints. A total of 2386 pharmacophore models for 819 different GPCRs (99 % coverage (819/825)) were generated and are available at http://bsb.kiz.ac.cn/GPCRPMD. PMID:27491793

  6. Pharmacophore modeling and molecular dynamics simulation to identify the critical chemical features against human sirtuin 2 inhibitors

    NASA Astrophysics Data System (ADS)

    Sakkiah, Sugunadevi; Baek, Ayoung; Lee, Keun Woo

    2012-03-01

    Sirtuin 2 (SIRT2) is one of the emerging targets in chemotherapy field and mainly associated with many diseases such as cancer and Parkinson's. Hence, quantitative hypothesis was developed using Discovery Studio v2.5. Top ten resultant hypotheses were generated, among them Hypo1 was selected as a best hypothesis based on the statistical parameters like high cost difference (52), lowest RMS (0.71), and good correlation coefficient (0.96). Hypo1 has been validated by using well known methodologies such as Fischer's randomization method (95% confidence level), test set which has shown the correlation coefficient of 0.93 as well as the goodness of hit (0.65), and enrichment factor (8.80). All the above statistical validations confirm that the chemical features in Hypo1 (1 hydrogen bond acceptor, 1 hydrophobic, and 2 ring aromatic features) was able to inhibit the function of SIRT2. Hence, Hypo1 was used as a query in virtual screening to find a novel scaffolds by screening the various chemical databases. The screened molecules from the databases were checked for the ADMET as well as the drug-like properties. Due to the lack of SIRT2-ligand complex structure in PDB, molecular docking and molecular dynamics (MD) simulation was carried out to find the suitable orientation of ligand in the active site. The representative structure from MD simulations was used as a receptor to dock the molecules which passed the drug-like properties from the virtual screening. Finally, 29 compounds were selected as a potent candidate leads based on the interactions with the active site residues of SIRT2. Thus, the resultant pharmacophore can be used to discover and design the SIRT2 inhibitors with desired biological activity.

  7. Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases.

    PubMed

    Kaserer, Teresa; Beck, Katharina R; Akram, Muhammad; Odermatt, Alex; Schuster, Daniela

    2015-01-01

    Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship analysis and selectivity profiling. In addition, compound-target interactions associated with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are associated with specific pathological conditions, and pharmacological modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biological functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies. PMID:26703541

  8. Pharmacophore modeling of cytochromes P450.

    PubMed

    de Groot, Marcel J; Ekins, Sean

    2002-03-31

    Understanding the binding of ligands in the active site of a membrane-bound protein is difficult in the absence of a crystal structure. When these proteins are the enzymes involved in drug metabolism, it leaves little option but to use site-directed mutagenesis and in vitro studies to provide critical information relating to determinants of binding affinity. Pharmacophore models and three-dimensional quantitative structure-activity relationships have been used either alone or in combination with protein homology models to provide this information for cytochrome P450s. At present, their application has been directed to the major enzymes but this may escalate in future as more in vitro data are generated for other P450s. The following review outlines the methodologies and models as well as future prospects for applying these technologies to P450s in the hope that future drugs will be selected with increased metabolic stability and fewer incidences of undesirable drug-drug interactions. PMID:11922953

  9. Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors.

    PubMed

    Bharatham, Kavitha; Bharatham, Nagakumar; Lee, Keun Woo

    2007-05-01

    A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 microM, was selected as a training set. Hypol, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypol) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypol performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypol model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors. PMID:17615669

  10. Tubulin inhibitors: pharmacophore modeling, virtual screening and molecular docking

    PubMed Central

    Niu, Miao-miao; Qin, Jing-yi; Tian, Cai-ping; Yan, Xia-fei; Dong, Feng-gong; Cheng, Zheng-qi; Fida, Guissi; Yang, Man; Chen, Haiyan; Gu, Yue-qing

    2014-01-01

    Aim: To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities. Methods: Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment (MOE) software and to biological evaluation in vitro. Results: Hypo1 was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient (0.9582), largest cost difference (70.905) and lowest RMSD value (0.6977). Hypo1 consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypo1 was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypo1 was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies <-4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro. Conclusion: Hypo1 is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities. PMID:24909516

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

    PubMed

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

    2013-09-01

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

  12. Potent Human Telomerase Inhibitors: Molecular Dynamic Simulations, Multiple Pharmacophore-Based Virtual Screening, and Biochemical Assays.

    PubMed

    Shirgahi Talari, Faezeh; Bagherzadeh, Kowsar; Golestanian, Sahand; Jarstfer, Michael; Amanlou, Massoud

    2015-12-28

    Telomere maintenance is a universal cancer hallmark, and small molecules that disrupt telomere maintenance generally have anticancer properties. Since the vast majority of cancer cells utilize telomerase activity for telomere maintenance, the enzyme has been considered as an anticancer drug target. Recently, rational design of telomerase inhibitors was made possible by the determination of high resolution structures of the catalytic telomerase subunit from a beetle and subsequent molecular modeling of the human telomerase complex. A hybrid strategy including docking, pharmacophore-based virtual screening, and molecular dynamics simulations (MDS) were used to identify new human telomerase inhibitors. Docking methodology was applied to investigate the ssDNA telomeric sequence and two well-known human telomerase inhibitors' (BIBR1532 and MST-312) modes of interactions with hTERT TEN domain. Subsequently molecular dynamic simulations were performed to monitor and compare hTERT TEN domain, TEN-ssDNA, TEN-BIBR1532, TEN-MST-312, and TEN-ssDNA-BIBR1532 behavior in a dynamic environment. Pharmacophore models were generated considering the inhibitors manner in the TEN domain anchor site. These exploratory studies identified several new potent inhibitors whose IC50 values were generated experimentally in a low micromolar range with the aid of biochemical assays, including both the direct telomerase and the telomeric repeat amplification protocol (TRAP) assays. The results suggest that the current models of human telomerase are useful templates for rational inhibitor design. PMID:26529120

  13. Pharmacophore Modelling and Synthesis of Quinoline-3-Carbohydrazide as Antioxidants

    PubMed Central

    El Bakkali, Mustapha; Ismaili, Lhassane; Tomassoli, Isabelle; Nicod, Laurence; Pudlo, Marc; Refouvelet, Bernard

    2011-01-01

    From well-known antioxidants agents, we developed a first pharmacophore model containing four common chemical features: one aromatic ring and three hydrogen bond acceptors. This model served as a template in virtual screening of Maybridge and NCI databases that resulted in selection of sixteen compounds. The selected compounds showed a good antioxidant activity measured by three chemical tests: DPPH radical, OH° radical, and superoxide radical scavenging. New synthetic compounds with a good correlation with the model were prepared, and some of them presented a good antioxidant activity. PMID:25954520

  14. Pharmacophore Model for Wnt/Porcupine Inhibitors and Its Use in Drug Design.

    PubMed

    Poulsen, Anders; Ho, Soo Yei; Wang, Weiling; Alam, Jenefer; Jeyaraj, Duraiswamy A; Ang, Shi Hua; Tan, Eldwin Sum Wai; Lin, Grace Ruiting; Cheong, Vivien Wei Wen; Ke, Zhiyuan; Lee, May Ann; Keller, Thomas H

    2015-07-27

    Porcupine is a component of the Wnt pathway which regulates cell proliferation, migration, stem cell self-renewal, and differentiation. The Wnt pathway has been shown to be dysregulated in a variety of cancers. Porcupine is a membrane bound O-acyltransferase that palmitoylates Wnt. Inhibiting porcupine blocks the secretion of Wnt and effectively inhibits the Wnt pathway. Using high throughput screening, we have identified a number of novel porcupine inhibitors with diverse scaffolds. The pharmacophore requirements for our porcupine inhibitors were elucidated, and a pharmacophore model is proposed. Our compounds as well as all currently published porcupine inhibitors may be fitted to this model in low energy conformations with good superimposition of the pharmacophore elements. The model also explains the stereochemical requirements of our chiral porcupine inhibitors. The pharmacophore model was successfully used for designing 3 new series of porcupine inhibitors having a tricyclic xantine, a phtalimide, or a piperidine-maleimide scaffold. PMID:26024410

  15. 3D pharmacophore models for thromboxane A(2) receptor antagonists.

    PubMed

    Wei, Jing; Liu, Yixi; Wang, Songqing

    2009-10-01

    Thromboxane A(2) (TXA(2)) is an endogenous arachidonic acid derivative closely correlated to thrombosis and other cardiovascular diseases. The action of TXA(2) can be effectively inhibited with TXA(2) receptor antagonists (TXRAs). Previous studies have attempted to describe the interactions between the TXA(2) receptor and its ligands, but their conclusions are still controversial. In this study, ligand-based computational drug design is used as a new and effective way to investigate the structure-activity relationship of TXRAs. Three-dimensional pharmacophore models of TXRAs were built with HypoGenRefine and HipHop modules in CATALYST software. The optimal HypoGenRefine model was developed on the basis of 25 TXRAs. It consists of two hydrophobic groups, one aromatic ring, one hydrogen-bond acceptor and four excluded volumes. The optimal HipHop model contains two hydrophobic groups and two hydrogen-bond acceptors. These models describe the key structure-activity relationship of TXRAs, can predict their activities, and can thus be used to design novel antagonists. PMID:19263096

  16. A Combination of Receptor-Based Pharmacophore Modeling & QM Techniques for Identification of Human Chymase Inhibitors

    PubMed Central

    Arooj, Mahreen; Sakkiah, Sugunadevi; Kim, Songmi; Arulalapperumal, Venkatesh; Lee, Keun Woo

    2013-01-01

    Inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, and fibrotic disorders. To find novel and potent chymase inhibitors and to provide a new idea for drug design, we used both ligand-based and structure-based methods to perform the virtual screening(VS) of commercially available databases. Different pharmacophore models generated from various crystal structures of enzyme may depict diverse inhibitor binding modes. Therefore, multiple pharmacophore-based approach is applied in this study. X-ray crystallographic data of chymase in complex with different inhibitors were used to generate four structure–based pharmacophore models. One ligand–based pharmacophore model was also developed from experimentally known inhibitors. After successful validation, all pharmacophore models were employed in database screening to retrieve hits with novel chemical scaffolds. Drug-like hit compounds were subjected to molecular docking using GOLD and AutoDock. Finally four structurally diverse compounds with high GOLD score and binding affinity for several crystal structures of chymase were selected as final hits. Identification of final hits by three different pharmacophore models necessitates the use of multiple pharmacophore-based approach in VS process. Quantum mechanical calculation is also conducted for analysis of electrostatic characteristics of compounds which illustrates their significant role in driving the inhibitor to adopt a suitable bioactive conformation oriented in the active site of enzyme. In general, this study is used as example to illustrate how multiple pharmacophore approach can be useful in identifying structurally diverse hits which may bind to all possible bioactive conformations available in the active site of enzyme. The strategy used in the current study could be appropriate to design drugs for other enzymes as well. PMID:23658661

  17. Identification of novel inhibitors of Daboia russelli phospholipase A2 using the combined pharmacophore modeling approach.

    PubMed

    Ramakrishnan, Chandrasekaran; Joshi, Vikram; Joseph, Joseph Mavelithuruthel; Vishwanath, Bannikuppe S; Velmurugan, Devadasan

    2014-10-01

    Crystal structures available for Daboia russelli venom PLA(2) confirm that it undergoes dimerization with asymmetry and hence difference in the conformation of active site of the two subunits. The active site of subunit A is open and that of subunit B is closed. Pharmacophore models were generated based on the interaction of different types of inhibitors with their preferred subsites in the active site of subunit A. Particularly, the features responsible for recognizing subsites 1-3 and those of subsites 4-6 were combined as these two are involving in inflammation and anticoagulation processes, respectively. Pharmacophore model was edited to make the geometry suitable for the active site of both the subunits A and B. Final model is validated and subjected for screening a library of druglike compounds. Eight compounds were shortlisted and subjected for molecular docking and dynamics simulation to assess their binding mode with both the subunits. Based on the hydrophobic interactions and binding free energy, four compounds were selected for further biochemical assay. The overall results suggest that two compounds can bind both the subunits of PLA(2) of Daboia russelli venom in spite of its aggregated form and other two inhibit structurally very similar Naja naja PLA(2). PMID:24703201

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

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2016-04-01

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

  19. Chemical Structure-Biological Activity Models for Pharmacophores' 3D-Interactions.

    PubMed

    Putz, Mihai V; Duda-Seiman, Corina; Duda-Seiman, Daniel; Putz, Ana-Maria; Alexandrescu, Iulia; Mernea, Maria; Avram, Speranta

    2016-01-01

    Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners' (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. PMID:27399692

  20. Pharmacophore Modeling for Anti-Chagas Drug Design Using the Fragment Molecular Orbital Method

    PubMed Central

    Ohno, Kazuki; Orita, Masaya; Inoue, Masayuki; Shiba, Tomoo; Harada, Shigeharu; Honma, Teruki; Balogun, Emmanuel Oluwadare; da Rocha, Josmar Rodrigues; Montanari, Carlos Alberto; Kita, Kiyoshi; Sekijima, Masakazu

    2015-01-01

    Background Chagas disease, caused by the parasite Trypanosoma cruzi, is a neglected tropical disease that causes severe human health problems. To develop a new chemotherapeutic agent for the treatment of Chagas disease, we predicted a pharmacophore model for T. cruzi dihydroorotate dehydrogenase (TcDHODH) by fragment molecular orbital (FMO) calculation for orotate, oxonate, and 43 orotate derivatives. Methodology/Principal Findings Intermolecular interactions in the complexes of TcDHODH with orotate, oxonate, and 43 orotate derivatives were analyzed by FMO calculation at the MP2/6-31G level. The results indicated that the orotate moiety, which is the base fragment of these compounds, interacts with the Lys43, Asn67, and Asn194 residues of TcDHODH and the cofactor flavin mononucleotide (FMN), whereas functional groups introduced at the orotate 5-position strongly interact with the Lys214 residue. Conclusions/Significance FMO-based interaction energy analyses revealed a pharmacophore model for TcDHODH inhibitor. Hydrogen bond acceptor pharmacophores correspond to Lys43 and Lys214, hydrogen bond donor and acceptor pharmacophores correspond to Asn67 and Asn194, and the aromatic ring pharmacophore corresponds to FMN, which shows important characteristics of compounds that inhibit TcDHODH. In addition, the Lys214 residue is not conserved between TcDHODH and human DHODH. Our analysis suggests that these orotate derivatives should preferentially bind to TcDHODH, increasing their selectivity. Our results obtained by pharmacophore modeling provides insight into the structural requirements for the design of TcDHODH inhibitors and their development as new anti-Chagas drugs. PMID:25961853

  1. A new insight into mushroom tyrosinase inhibitors: docking, pharmacophore-based virtual screening, and molecular modeling studies.

    PubMed

    Bagherzadeh, Kowsar; Shirgahi Talari, Faezeh; Sharifi, Amirhossein; Ganjali, Mohammad Reza; Saboury, Ali Akbar; Amanlou, Massoud

    2015-01-01

    Tyrosinase, a widely spread enzyme in micro-organisms, animals, and plants, participates in two rate-limiting steps in melanin formation pathway which is responsible for skin protection against UV lights' harm whose functional deficiency result in serious dermatological diseases. This enzyme seems to be responsible for neuromelanin formation in human brain as well. In plants, the enzyme leads the browning pathway which is commonly observed in injured tissues that is economically very unfavorable. Among different types of tyrosinase, mushroom tyrosinase has the highest homology with the mammalian tyrosinase and the only commercial tyrosinase available. In this study, ligand-based pharmacophore drug discovery method was applied to rapidly identify mushroom tyrosinase enzyme inhibitors using virtual screening. The model pharmacophore of essential interactions was developed and refined studying already experimentally discovered potent inhibitors employing Docking analysis methodology. After pharmacophore virtual screening and binding modes prediction, 14 compounds from ZINC database were identified as potent inhibitors of mushroom tyrosinase which were classified into five groups according to their chemical structures. The inhibition behavior of the discovered compounds was further studied through Classical Molecular Dynamic Simulations and the conformational changes induced by the presence of the studied ligands were discussed and compared to those of the substrate, tyrosine. According to the obtained results, five novel leads are introduced to be further optimized or directly used as potent inhibitors of mushroom tyrosinase. PMID:24601849

  2. Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents

    PubMed Central

    Cele, Favourite N; Ramesh, Muthusamy; Soliman, Mahmoud ES

    2016-01-01

    A novel virtual screening approach is implemented herein, which is a further improvement of our previously published “target-bound pharmacophore modeling approach”. The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry. PMID:27114700

  3. Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents.

    PubMed

    Cele, Favourite N; Ramesh, Muthusamy; Soliman, Mahmoud Es

    2016-01-01

    A novel virtual screening approach is implemented herein, which is a further improvement of our previously published "target-bound pharmacophore modeling approach". The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry. PMID:27114700

  4. Pharmacophore modeling and virtual screening studies of checkpoint kinase 1 inhibitors.

    PubMed

    Chen, Jin-Juan; Liu, Ting-Lin; Yang, Li-Jun; Li, Lin-Li; Wei, Yu-Quan; Yang, Sheng-Yong

    2009-07-01

    In this study, chemical feature-based 3-dimensional (3D) pharmacophore models of Checkpoint kinase 1 (Chk1) inhibitors were developed based on the known inhibitors of Chk1. The best pharmacophore model Hypo1 was characterized by the best correlation coefficient (0.9577), and the lowest root mean square deviation (0.8871). Hypo1 consists of one hydrogen-bond acceptor, one hydrogen-bond donor, and two hydrophobic features, as well as one excluded volume. This pharmacophore model was further validated by both test set and cross validation methods. A comparison analysis of Hypo1 with chemical features in the active site of Chk1 indicates that the pharmacophore model Hypo1 can correctly reflect the interactions between Chk1 and its ligands. Then Hypo1 was used to screen chemical databases, including Specs and Chinese Nature Product Database (CNPD) for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits. Finally some of the most potent (estimated) compounds were selected from the final refined hits and suggested for further experimental investigation. PMID:19571415

  5. Three dimensional pharmacophore modeling of human CYP17 inhibitors. Potential agents for prostate cancer therapy.

    PubMed

    Clement, Omoshile O; Freeman, Clive M; Hartmann, Rolf W; Handratta, Venkatesh D; Vasaitis, Tadas S; Brodie, Angela M H; Njar, Vincent C O

    2003-06-01

    We report here a molecular modeling investigation of steroidal and nonsteroidal inhibitors of human cytochrome P450 17alpha-hydroxylase-17,20-lyase (CYP17). Using the pharmacophore perception technique, we have generated common-feature pharmacophore model(s) to explain the putative binding requirements for two classes of human CYP17 inhibitors. Common chemical features in the steroid and nonsteroid human CYP17 enzyme inhibitors, as deduced by the Catalyst/HipHop program, are one to two hydrogen bond acceptors (HBAs) and three hydrophobic groups. For azole-steroidal ligands, the 3beta-OH group of ring A and the N-3 of the azole ring attached to ring D at C-17 act as hydrogen bond acceptors. A model that permits hydrogen bond interaction between the azole functionality on ring D and the enzyme is consistent with experimental deductions for type II CYP17 inhibitors where a sixth ligating atom interacts with Fe(II) of heme. In general, pharmacophore models derived for steroid and nonsteroidal compounds bear striking similarities to all azole sites mapping the HBA functionality and to three hydrophobic features describing the hydrophobic interactions between the ligands and the enzyme. Using the pharmacophore model derived for azole-steroidal inhibitors as a 3D search query against several 3D multiconformational Catalyst formatted databases, we identified several steroidal compounds with potential inhibition of this enzyme. Biological testing of some of these compounds show low to high inhibitory potency against the human CYP17 enzyme. This shows the potential of our pharmacophore model in identifying new and potent CYP17 inhibitors. Further refinement of the model is in progress with a view to identifying and optimizing new leads. PMID:12773039

  6. Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives, a new class of alpha-glucosidase inhibitors.

    PubMed

    Bharatham, Kavitha; Bharatham, Nagakumar; Park, Ki Hun; Lee, Keun Woo

    2008-06-01

    Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for alpha-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae alpha-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation, all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as alpha-glucosidase inhibitors. PMID:18096420

  7. Pharmacophore modeling of substituted 1,2,4-Trioxanes for quantitative prediction of their antimalarial activity.

    PubMed

    Gupta, Amit K; Chakroborty, S; Srivastava, Kumkum; Puri, Sunil K; Saxena, Anil K

    2010-08-23

    A pharmacophore model has been developed for determining the essential structural requirements for antimalarial activity from the eight series of substituted 1,2,4-trioxanes. The best pharmacophore model possessing two aliphatic hydrophobic, one aromatic hydrophobic, one hydrogen-bond (H-bond) acceptor, and one H-bond acceptor (lipid) feature for antimalarial activity showed an excellent correlation coefficient for the training (r(2)(training) = 0.85) and a fair correlation coefficient for the test set (r(2)(test) = 0.51) molecules. The model predicts well to other known substituted 1,2,4-trioxanes including those which either are drugs or are undergoing clinical trials. In order to further validate this model, five substituted 1,2,4-trioxanes were synthesized from the generated focused library and screened for antimalarial activity. The observed activity of these molecules was consistent with the pharmacophore model, suggesting that the model may be useful in the design of potent antimalarial agents. PMID:20726605

  8. Pharmacophore modeling and in silico toxicity assessment of potential anticancer agents from African medicinal plants

    PubMed Central

    Ntie-Kang, Fidele; Simoben, Conrad Veranso; Karaman, Berin; Ngwa, Valery Fuh; Judson, Philip Neville; Sippl, Wolfgang; Mbaze, Luc Meva’a

    2016-01-01

    Molecular modeling has been employed in the search for lead compounds of chemotherapy to fight cancer. In this study, pharmacophore models have been generated and validated for use in virtual screening protocols for eight known anticancer drug targets, including tyrosine kinase, protein kinase B β, cyclin-dependent kinase, protein farnesyltransferase, human protein kinase, glycogen synthase kinase, and indoleamine 2,3-dioxygenase 1. Pharmacophore models were validated through receiver operating characteristic and Güner–Henry scoring methods, indicating that several of the models generated could be useful for the identification of potential anticancer agents from natural product databases. The validated pharmacophore models were used as three-dimensional search queries for virtual screening of the newly developed AfroCancer database (~400 compounds from African medicinal plants), along with the Naturally Occurring Plant-based Anticancer Compound-Activity-Target dataset (comprising ~1,500 published naturally occurring plant-based compounds from around the world). Additionally, an in silico assessment of toxicity of the two datasets was carried out by the use of 88 toxicity end points predicted by the Lhasa’s expert knowledge-based system (Derek), showing that only an insignificant proportion of the promising anticancer agents would be likely showing high toxicity profiles. A diversity study of the two datasets, carried out using the analysis of principal components from the most important physicochemical properties often used to access drug-likeness of compound datasets, showed that the two datasets do not occupy the same chemical space. PMID:27445461

  9. Pharmacophore model of the quercetin binding site of the SIRT6 protein.

    PubMed

    Ravichandran, S; Singh, N; Donnelly, D; Migliore, M; Johnson, P; Fishwick, C; Luke, B T; Martin, B; Maudsley, S; Fugmann, S D; Moaddel, R

    2014-04-01

    SIRT6 is a histone deacetylase that has been proposed as a potential therapeutic target for metabolic disorders and the prevention of age-associated diseases. We have previously reported on the identification of quercetin and vitexin as SIRT6 inhibitors, and studied structurally related flavonoids including luteolin, kaempferol, apigenin and naringenin. It was determined that the SIRT6 protein remained active after immobilization and that a single frontal displacement could correctly predict the functional activity of the immobilized enzyme. The previous study generated a preliminary pharmacophore for the quercetin binding site on SIRT6, containing 3 hydrogen bond donors and one hydrogen bond acceptor. In this study, we have generated a refined pharmacophore with an additional twelve quercetin analogs. The resulting model had a positive linear behavior between the experimental elution time verses the fit values obtained from the model with a correlation coefficient of 0.8456. PMID:24491483

  10. Identification of ligand features essential for HDACs inhibitors by pharmacophore modeling.

    PubMed

    Chen, Ya-Dong; Jiang, Yong-Jun; Zhou, Jian-Wei; Yu, Qing-Sen; You, Qi-Dong

    2008-04-01

    Histone deacetylases (HDACs) enzyme plays a significant role in transcriptional regulation by modifying the core histones of the nucleosome. It has emerged as an important therapeutic target for the treatment of cancer and other diseases. Inhibitors of HDACs become a new class of anticancer agents and have provoked much interest amongst pharmacologists and cancer researchers. To facilitate the discovery of specific HDACs inhibitors, a 3D chemical-feature-based QSAR pharmacophore model was developed and was well consistent with the structure-functional requirements for the binding of the HDAC inhibitors. Using this model, the interactions between the benzamide MS-275 and HDAC were explored. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme-inhibitor interaction pattern identified from molecular docking. PMID:18061500

  11. Pharmacophore model of the quercetin binding site of the SIRT6 protein

    PubMed Central

    Ravichandran, S.; Singh, N.; Donnelly, D.; Migliore, M.; Johnson, P.; Fishwick, C.; Luke, Brian T.; Martin, B.; Maudsley, S.; Fugmann, S. D.; Moaddel, R.

    2014-01-01

    SIRT6 is a histone deacetylase that has been proposed as a potential therapeutic target for metabolic disorders and the prevention of age-associated diseases. We have previously reported on the identification of quercetin and vitexin as SIRT6 inhibitors, and studied structurally related flavonoids including luteolin, kaempferol, apigenin and naringenin. It was determined that the SIRT6 protein remained active after immobilization and that a single frontal displacement could correctly predict the functional activity of the immobilized enzyme. The previous study generated a preliminary pharmacophore for the quercetin binding site on SIRT6, containing 3 hydrogen bond donors and one hydrogen bond acceptor. In this study, we have generated a refined pharmacophore with an additional twelve quercetin analogs. The resulting model had a positive linear behavior between the experimental elution time verses the fit values obtained from the model with a correlation coefficient of 0.8456. PMID:24491483

  12. Pharmacophore modeling studies of type I and type II kinase inhibitors of Tie2.

    PubMed

    Xie, Qing-Qing; Xie, Huan-Zhang; Ren, Ji-Xia; Li, Lin-Li; Yang, Sheng-Yong

    2009-02-01

    In this study, chemical feature based pharmacophore models of type I and type II kinase inhibitors of Tie2 have been developed with the aid of HipHop and HypoRefine modules within Catalyst program package. The best HipHop pharmacophore model Hypo1_I for type I kinase inhibitors contains one hydrogen-bond acceptor, one hydrogen-bond donor, one general hydrophobic, one hydrophobic aromatic, and one ring aromatic feature. And the best HypoRefine model Hypo1_II for type II kinase inhibitors, which was characterized by the best correlation coefficient (0.976032) and the lowest RMSD (0.74204), consists of two hydrogen-bond donors, one hydrophobic aromatic, and two general hydrophobic features, as well as two excluded volumes. These pharmacophore models have been validated by using either or both test set and cross validation methods, which shows that both the Hypo1_I and Hypo1_II have a good predictive ability. The space arrangements of the pharmacophore features in Hypo1_II are consistent with the locations of the three portions making up a typical type II kinase inhibitor, namely, the portion occupying the ATP binding region (ATP-binding-region portion, AP), that occupying the hydrophobic region (hydrophobic-region portion, HP), and that linking AP and HP (bridge portion, BP). Our study also reveals that the ATP-binding-region portion of the type II kinase inhibitors plays an important role to the bioactivity of the type II kinase inhibitors. Structural modifications on this portion should be helpful to further improve the inhibitory potency of type II kinase inhibitors. PMID:19138543

  13. Pharmacophore modeling of dual angiotensin II and endothelin A receptor antagonists.

    PubMed

    Xue, Wei-Zhe; Lü, Wei; Zhou, Zhi-Ming; Wang, Zhan-Li

    2009-09-01

    Three-dimensional pharmacophore models were generated for AT1 and ET(A) receptors based on highly selective AT1 and ET(A) antagonists using the program Catalyst/HipHop. Both the best pharmacophore model for selective AT1 antagonists (Hypo-AT(1)-7) and ETA antagonists (Hypo-ET(A)-1) were obtained through a careful validation process. All five features contained in Hypo-AT(1)-7 and Hypo-ET(A)-1 (hydrogen-bond acceptor (A), hydrophobic aliphatic (Z), negative ionizable (N), ring aromatic (R), and hydrophobic aromatic (Y)) seem to be essential for antagonists in terms of binding activity. Dual AT1 and ET(A) receptor antagonists (DARAs) can map to both Hypo-AT(1)-7 and Hypo-ET(A)-1, separately. Comparison of Hypo-AT(1)-7 and Hypo-ET(A)-1, not only AT1 and ET(A) antagonist pharmacophore models consist of essential features necessary for compounds to be highly active and selective toward their corresponding receptor, but also have something in common. The results in this study will act as a valuable tool for designing and researching structural relationship of novel dual AT1 and ET(A) receptor antagonists. PMID:20055175

  14. Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors.

    PubMed

    Wang, Hui-Yuan; Cao, Zhi-Xing; Li, Lin-Li; Jiang, Pei-Du; Zhao, Ying-Lan; Luo, Shi-Dong; Yang, Li; Wei, Yu-Quan; Yang, Sheng-Yong

    2008-09-15

    Pharmacophore models of Polo-like kinase-1 (PLK1) inhibitors have been established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9895), consists of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic feature, and one hydrophobic aliphatic feature. Hypo1 was further validated by test set and cross validation method. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, a total of 20 compounds were selected and have been shifted to in vitro and in vivo studies. As far as we know, this is the first report on the pharmacophore modeling even the first publicly reported virtual screening study of PLK1 inhibitors. PMID:18762425

  15. Influence of the conditions in pharmacophore generation, scoring, and 3D database search for chemical feature-based pharmacophore models: one application study of ETA- and ETB-selective antagonists.

    PubMed

    Cucarull-González, Joan R; Laggner, Christian; Langer, Thierry

    2006-01-01

    Using the commercial pharmacophore modeling suite Catalyst, we have studied the influence of the compare.scaledMultiBlobFeatureErrors . Catalyst parameter. The influence of this parameter has been studied in pharmacophore generation, hypothesis scoring, and database searching. This parameter, introduced in Catalyst 4.7, changed its default value in Catalyst 4.8, and it strongly influences the statistical quality of pharmacophore generation, scoring of the hypotheses, and database searching. Two different pharmacophore models have been constructed for the ETA and ETB receptor antagonists. Both models contain one positive ionizable, one negative ionizable, one hydrogen-bond acceptor, one hydrophobic aromatic, and one hydrophobic aliphatic feature. The models have been compared, and some differences in the position of the hydrogen-bond acceptor in the putative binding pocket have been highlighted. PMID:16711764

  16. Pharmacophore modeling and in silico screening for new P450 19 (aromatase) inhibitors.

    PubMed

    Schuster, Daniela; Laggner, Christian; Steindl, Theodora M; Palusczak, Anja; Hartmann, Rolf W; Langer, Thierry

    2006-01-01

    Cytochrome P450 19 (P450 19, aromatase) constitutes a successful target for the treatment of breast cancer. This study analyzes chemical features common to P450 19 inhibitors to develop ligand-based, selective pharmacophore models for this enzyme. The HipHop and HypoRefine algorithms implemented in the Catalyst software package were employed to create both common feature and quantitative models. The common feature model for P450 19 includes two ring aromatic features in its core and two hydrogen bond acceptors at the ends. The models were used as database search queries to identify active compounds from the NCI database. PMID:16711749

  17. Pharmacophore modeling and virtual screening for designing potential 5-lipoxygenase inhibitors.

    PubMed

    Aparoy, P; Kumar Reddy, K; Kalangi, Suresh K; Chandramohan Reddy, T; Reddanna, P

    2010-02-01

    Inhibitors of the 5-Lipoxygenase (5-LOX) pathway have a therapeutic potential in a variety of inflammatory disorders such as asthma. In this study, chemical feature based pharmacophore models of inhibitors of 5-LOX have been developed with the aid of HipHop and HypoGen modules within Catalyst program package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.97), consists of two hydrogen-bond acceptors, one hydrophobic feature and one ring aromatic feature. Hypo1 was further validated by test set and cross validation method. The application of the model shows great success in predicting the activities of 65 known 5-LOX inhibitors in our test set with a correlation coefficient of 0.85 with a cross validation of 95% confidence level, proving that the model is reliable in identifying structurally diverse compounds for inhibitory activity against 5-LOX. Furthermore, Hypo1 was used as a 3D query for screening Maybridge and NCI databases within catalyst and also drug like compounds obtained from Enamine Ltd, which follow Lipinski's rule of five. The hit compounds were subsequently subjected to filtering by docking and visualization, to identify the potential lead molecules. Finally 5 potential lead compounds, identified in the above process, were evaluated for their inhibitory activities. These studies resulted in the identification of two compounds with potent inhibition of 5-LOX activity with IC(50) of 14 microM and 35 microM, respectively. These studies thus validate the pharmacophore model generated and suggest the usefulness of the model in screening of various small molecule libraries and identification of potential lead compounds for 5-LOX inhibition. PMID:20045317

  18. Pharmacophore modeling, virtual screening, docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors.

    PubMed

    Vyas, Vivek K; Ghate, Manjunath; Goel, Ashutosh

    2013-05-01

    Protein kinase B (PKB) is a key mediator of proliferation and survival pathways that are critical for cancer growth. Therefore, inhibitors of PKB are useful agents for the treatment of cancer. Herein, we describe pharmacophore-based virtual screening combined with docking study as a rational strategy for identification of novel hits or leads. Pharmacophore models of PKB β inhibitors were established using the DISCOtech and refined with GASP from compounds with IC50 values ranging from 2.2 to 246nM. The best pharmacophore model consists of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) site and two hydrophobic (HY) features. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner-Henry (GH) scoring methods indicated that the model-3 was statistically valuable and reliable in identifying PKB β inhibitors. Pharmacophore model as a 3D search query was searched against NCI database. Several compounds with different structures (scaffolds) were retrieved as hits. Molecules with a Qfit value of more than 95 and three other known inhibitors were docked in the active site of PKB to further explore the binding mode of these compounds. Finally in silico pharmacokinetic and toxicities were predicted for active hit molecules. The hits reported here showed good potential to be PKB β inhibitors. PMID:23507201

  19. Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors.

    PubMed

    Chen, Xiu-Mei; Lu, Tao; Lu, Shuai; Li, Hui-Fang; Yuan, Hao-Liang; Ran, Ting; Liu, Hai-Chun; Chen, Ya-Dong

    2010-07-01

    Checkpoint kinase 1 (Chk1), a member of the serine/threonine kinase family, is an attractive therapeutic target for anticancer combination therapy. A structure-based modeling approach complemented with shape components was pursued to develop a reliable pharmacophore model for ATP-competitive Chk1 inhibitors. Common chemical features of the pharmacophore model were derived by clustering multiple structure-based pharmacophore features from different Chk1-ligand complexes in comparable binding modes. The final model consisted of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD), two hydrophobic (HY) features, several excluded volumes and shape constraints. In the validation study, this feature-shape query yielded an enrichment factor of 9.196 and performed fairly well at distinguishing active from inactive compounds, suggesting that the pharmacophore model can serve as a reliable tool for virtual screening to facilitate the discovery of novel Chk1 inhibitors. Besides, these pharmacophore features were assumed to be essential for Chk1 inhibitors, which might be useful for the identification of potential Chk1 inhibitors. PMID:20020310

  20. In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations.

    PubMed

    Rakers, Christin; Schumacher, Fabian; Meinl, Walter; Glatt, Hansruedi; Kleuser, Burkhard; Wolber, Gerhard

    2016-01-01

    Acting during phase II metabolism, sulfotransferases (SULTs) serve detoxification by transforming a broad spectrum of compounds from pharmaceutical, nutritional, or environmental sources into more easily excretable metabolites. However, SULT activity has also been shown to promote formation of reactive metabolites that may have genotoxic effects. SULT subtype 1E1 (SULT1E1) was identified as a key player in estrogen homeostasis, which is involved in many physiological processes and the pathogenesis of breast and endometrial cancer. The development of an in silico prediction model for SULT1E1 ligands would therefore support the development of metabolically inert drugs and help to assess health risks related to hormonal imbalances. Here, we report on a novel approach to develop a model that enables prediction of substrates and inhibitors of SULT1E1. Molecular dynamics simulations were performed to investigate enzyme flexibility and sample protein conformations. Pharmacophores were developed that served as a cornerstone of the model, and machine learning techniques were applied for prediction refinement. The prediction model was used to screen the DrugBank (a database of experimental and approved drugs): 28% of the predicted hits were reported in literature as ligands of SULT1E1. From the remaining hits, a selection of nine molecules was subjected to biochemical assay validation and experimental results were in accordance with the in silico prediction of SULT1E1 inhibitors and substrates, thus affirming our prediction hypotheses. PMID:26542807

  1. Structure-Based Inhibitor Design for Evaluation of a CYP3A4 Pharmacophore Model.

    PubMed

    Kaur, Parminder; Chamberlin, A Richard; Poulos, Thomas L; Sevrioukova, Irina F

    2016-05-12

    Human cytochrome P450 3A4 (CYP3A4) is a key xenobiotic-metabolizing enzyme that oxidizes and clears the majority of drugs. CYP3A4 inhibition may lead to drug-drug interactions, toxicity, and other adverse effects but, in some cases, could be beneficial and enhance therapeutic efficiency of coadministered pharmaceuticals that are metabolized by CYP3A4. On the basis of our investigations of analogs of ritonavir, a potent CYP3A4 inactivator and pharmacoenhancer, we have built a pharmacophore model for a CYP3A4-specific inhibitor. This study is the first attempt to test this model using a set of rationally designed compounds. The functional and structural data presented here agree well with the proposed pharmacophore. In particular, we confirmed the importance of a flexible backbone, the H-bond donor/acceptor moiety, and aromaticity of the side group analogous to Phe-2 of ritonavir and demonstrated the leading role of hydrophobic interactions at the sites adjacent to the heme and phenylalanine cluster in the ligand binding process. The X-ray structures of CYP3A4 bound to the rationally designed inhibitors provide deeper insights into the mechanism of the CYP3A4-ligand interaction. Most importantly, two of our compounds (15a and 15b) that are less complex than ritonavir have comparable submicromolar affinity and inhibitory potency for CYP3A4 and, thus, could serve as templates for synthesis of second generation inhibitors for further evaluation and optimization of the pharmacophore model. PMID:26371436

  2. Discovery of potent inhibitors of pseudomonal quorum sensing via pharmacophore modeling and in silico screening.

    PubMed

    Taha, Mutasem O; Al-Bakri, Amal G; Zalloum, Waleed A

    2006-11-15

    HipHop-Refine was employed to derive a binding hypothesis for pseudomonal quorum sensing (QS) antagonists. The model was employed as 3D search query to screen the National Cancer Institute (NCI) database. One of the hits illustrated nanomolar QS inhibitory activity. The fact that this compound contained tetravalent lead (Pb) prompted us to evaluate the activities of phenyl mercuric nitrate and thimerosal, both fit the binding pharmacophore. The two mercurials illustrated nanomolar to low micromolar IC50 inhibitory values against pseudomonal QS. The three compounds represent a new class of QS inhibitors. PMID:16945524

  3. A Review of the Updated Pharmacophore for the Alpha 5 GABA(A) Benzodiazepine Receptor Model

    PubMed Central

    Clayton, Terry; Poe, Michael M.; Rallapalli, Sundari; Biawat, Poonam; Savić, Miroslav M.; Rowlett, James K.; Gallos, George; Emala, Charles W.; Kaczorowski, Catherine C.; Stafford, Douglas C.; Arnold, Leggy A.; Cook, James M.

    2015-01-01

    An updated model of the GABA(A) benzodiazepine receptor pharmacophore of the α5-BzR/GABA(A) subtype has been constructed prompted by the synthesis of subtype selective ligands in light of the recent developments in both ligand synthesis, behavioral studies, and molecular modeling studies of the binding site itself. A number of BzR/GABA(A) α5 subtype selective compounds were synthesized, notably α5-subtype selective inverse agonist PWZ-029 (1) which is active in enhancing cognition in both rodents and primates. In addition, a chiral positive allosteric modulator (PAM), SH-053-2′F-R-CH3 (2), has been shown to reverse the deleterious effects in the MAM-model of schizophrenia as well as alleviate constriction in airway smooth muscle. Presented here is an updated model of the pharmacophore for α5β2γ2 Bz/GABA(A) receptors, including a rendering of PWZ-029 docked within the α5-binding pocket showing specific interactions of the molecule with the receptor. Differences in the included volume as compared to α1β2γ2, α2β2γ2, and α3β2γ2 will be illustrated for clarity. These new models enhance the ability to understand structural characteristics of ligands which act as agonists, antagonists, or inverse agonists at the Bz BS of GABA(A) receptors. PMID:26682068

  4. Ligand-based pharmacophore model of N-Aryl and N-Heteroaryl piperazine alpha 1A-adrenoceptors antagonists using GALAHAD.

    PubMed

    Zhao, Xin; Yuan, Mu; Huang, Biyun; Ji, Hong; Zhu, Liu

    2010-09-01

    Computer aided drug discovery for selective antagonism effects on alpha(1A) subtypes of G-protein coupled receptors are important in the treatment of benign prostatic hyperplasia (BPH). Ligand-based pharmacophore models of N-Aryl and N-Heteroaryl piperazine alpha(1A)-antagonists were developed using two separate training sets. Pharmacophore models were generated using the flexible align method within the GALAHAD module, implemented in SYBYL8.1 software. The most significant pharmacophore hypothesis, characterized by the conflicting demands of maximizing pharmacophore consensus, maximizing steric consensus, and minimizing energy, consisted of one positive nitrogen center, one donor atom center, two acceptor atom centers, and two hydrophobic groups. The most active compound in each class training set showed a good fit with all features of the pharmacophore proposed. The resulting models also had something in common with the hypothesis using the Catalyst software reported in other publications. These alpha(1A) pharmacophore models could predict compounds well, both in the training set and the test set. The pharmacophore models were also validated by an external dataset using a portion of the ZINC database. A 3D-QSAR model using the pharmacophore model to align the compounds was established in this study. The CoMFA model with the cross-validated q(2) value of 0.735 revealed that the model was valid. Our research provides a valuable tool for designing new therapeutic compounds with desired biological activity. PMID:20538497

  5. Pharmacophore Modeling and Docking Studies on Some Nonpeptide-Based Caspase-3 Inhibitors

    PubMed Central

    Sharma, Simant; Basu, Arijit; Agrawal, R. K.

    2013-01-01

    Neurodegenerative disorders are major consequences of excessive apoptosis caused by a proteolytic enzyme known as caspase-3. Therefore, caspase-3 inhibition has become a validated therapeutic approach for neurodegenerative disorders. We performed pharmacophore modeling on some synthetic derivatives of caspase-3 inhibitors (pyrrolo[3,4-c]quinoline-1,3-diones) using PHASE 3.0. This resulted in the common pharmacophore hypothesis AAHRR.6 which might be responsible for the biological activity: two aromatic rings (R) mainly in the quinoline nucleus, one hydrophobic (H) group (CH3), and two acceptor (A) groups (–C=O). After identifying a valid hypothesis, we also developed an atom-based 3D-QSAR model applying the PLS algorithm. The developed model was statistically robust (q2 = 0.53; pred_r2 = 0.80). Additionally, we have performed molecular docking studies, cross-validated our results, and gained a deeper insight into its molecular recognition process. Our developed model may serve as a query tool for future virtual screening and drug designing for this particular target. PMID:24089669

  6. Pharmacophore modeling and docking studies on some nonpeptide-based caspase-3 inhibitors.

    PubMed

    Sharma, Simant; Basu, Arijit; Agrawal, R K

    2013-01-01

    Neurodegenerative disorders are major consequences of excessive apoptosis caused by a proteolytic enzyme known as caspase-3. Therefore, caspase-3 inhibition has become a validated therapeutic approach for neurodegenerative disorders. We performed pharmacophore modeling on some synthetic derivatives of caspase-3 inhibitors (pyrrolo[3,4-c]quinoline-1,3-diones) using PHASE 3.0. This resulted in the common pharmacophore hypothesis AAHRR.6 which might be responsible for the biological activity: two aromatic rings (R) mainly in the quinoline nucleus, one hydrophobic (H) group (CH₃), and two acceptor (A) groups (-C=O). After identifying a valid hypothesis, we also developed an atom-based 3D-QSAR model applying the PLS algorithm. The developed model was statistically robust (q² = 0.53; pred_r² = 0.80). Additionally, we have performed molecular docking studies, cross-validated our results, and gained a deeper insight into its molecular recognition process. Our developed model may serve as a query tool for future virtual screening and drug designing for this particular target. PMID:24089669

  7. A specific pharmacophore model of Aurora B kinase inhibitors and virtual screening studies based on it.

    PubMed

    Wang, Hui-Yuan; Li, Lin-Li; Cao, Zhi-Xing; Luo, Shi-Dong; Wei, Yu-Quan; Yang, Sheng-Yong

    2009-01-01

    In this study, 3D-pharmacophore models of Aurora B kinase inhibitors have been developed by using HipHop and HypoGen modules in Catalyst software package. The best pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9911), consists of one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic aliphatic moiety and one ring aromatic feature. Hypo1 was validated by test set and cross-validation methods. And the specificity of Hypo1 to Aurora B inhibitors was examined with the use of selective inhibitors against Aurora B and its paralogue Aurora A. The results clearly indicate that Hypo1 can differentiate selective inhibitors of Aurora B from those of Aurora A, and the ring aromatic feature likely plays some important roles for the specificity of Hypo1. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD) for identifying new inhibitors of Aurora B. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies to refine the retrieved hits, and some compounds selected from the top ranked hits have been suggested for further experimental assay studies. PMID:19152640

  8. Discovery of dual binding site acetylcholinesterase inhibitors identified by pharmacophore modeling and sequential virtual screening techniques.

    PubMed

    Gupta, Shikhar; Fallarero, Adyary; Järvinen, Päivi; Karlsson, Daniela; Johnson, Mark S; Vuorela, Pia M; Mohan, C Gopi

    2011-02-15

    Dual binding site acetylcholinesterase (AChE) inhibitors are promising for the treatment of Alzheimer's disease (AD). They alleviate the cognitive deficits and AD-modifying agents, by inhibiting the β-amyloid (Aβ) peptide aggregation, through binding to both the catalytic and peripheral anionic sites, the so called dual binding site of the AChE enzyme. In this Letter, chemical features based 3D-pharmacophore models were developed based on the eight potent and structurally diverse AChE inhibitors (I-VIII) obtained from high-throughput in vitro screening technique. The best 3D-pharmacophore model, Hypo1, consists of two hydrogen-bond acceptor lipid, one hydrophobe, and two hydrophobic aliphatic features obtained by Catalyst/HIPHOP algorithm adopted in Discovery studio program. Hypo1 was used as a 3D query in sequential virtual screening study to filter three small compound databases. Further, a total of nine compounds were selected and followed on in vitro analysis. Finally, we identified two leads--Specs1 (IC(50)=3.279 μM) and Spec2 (IC(50)=5.986 μM) dual binding site compounds from Specs database, having good AChE enzyme inhibitory activity. PMID:21273074

  9. Pharmacophore modeling, 3D-QSAR, and docking study of pyrozolo[1,5-a]pyridine/4,4-dimethylpyrazolone analogues as PDE4 selective inhibitors.

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2015-11-01

    Phosphodiesterases 4 enzyme is an attractive target for the design of anti-inflammatory and bronchodilator agents. In the present study pharmacophore and atom based 3D-QSAR studies were carried out for pyrozolo[1,5-a]pyridine/4,4-dimethylpyrazolone analogues. A five point pharmacophore model was developed using 52 molecules having pIC50 values ranging from 9.959 to 3.939. The best predictive pharmacophoric hypothesis AHHRR.3 was characterized by survival score (2.944), cross validated (r(2) = 0.8147), regression coefficient (R(2) = 0.9545) and Fisher ratio (F =173) with 4 component PLS factor. Results explained that one hydrogen bond acceptor, two aromatic rings and two hydrophobic groups are crucial for the PDE4 inhibition. The docking studies of all selected inhibitors in the active site of PDE4 showed crucial hydrogen bond interactions with Asp392, Asn395 Tyr233, and Gln443 residues. The pharmacophoric features R15 and R16 exhibited π-π stacking with His234, Phe414, and Phe446 residues. The generated model was further validated by carrying out the decoy test. The binding free energies of these inhibitors in the catalytic domain of 1XMU were calculated by the molecular mechanics/generalized Born surface area VSGB 2.0 method. The results of molecular dynamics simulation confirmed the extra precision docking-predicted priority for binding sites, the accuracy of docking, and the reliability of active conformations. Pyrozolo[1,5-a]pyridine/4,4-dimethylpyrazolone analogues in this study showed lower binding affinity toward PDE3A in comparison to PDE4. Outcomes of the present study provide insight in designing novel molecules with better PDE4 inhibitory activity. Graphical Abstract Pyrozolo[1,5-a]pyridines/4,4-dimethylpyrazolones. PMID:26499496

  10. Pharmacophore modeling, virtual screening and 3D-QSAR studies of 5-tetrahydroquinolinylidine aminoguanidine derivatives as sodium hydrogen exchanger inhibitors.

    PubMed

    Bhatt, Hardik G; Patel, Paresh K

    2012-06-01

    Sodium hydrogen exchanger (SHE) inhibitor is one of the most important targets in treatment of myocardial ischemia. In the course of our research into new types of non-acylguanidine, SHE inhibitory activities of 5-tetrahydroquinolinylidine aminoguanidine derivatives were used to build pharmacophore and 3D-QSAR models. Genetic Algorithm Similarity Program (GASP) was used to derive a 3D pharmacophore model which was used in effective alignment of data set. Eight molecules were selected on the basis of structure diversity to build 10 different pharmacophore models. Model 1 was considered as the best model as it has highest fitness score compared to other nine models. The obtained model contained two acceptor sites, two donor atoms and one hydrophobic region. Pharmacophore modeling was followed by substructure searching and virtual screening. The best CoMFA model, representing steric and electrostatic fields, obtained for 30 training set molecules was statistically significant with cross-validated coefficient (q(2)) of 0.673 and conventional coefficient (r(2)) of 0.988. In addition to steric and electrostatic fields observed in CoMFA, CoMSIA also represents hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. CoMSIA model was also significant with cross-validated coefficient (q(2)) and conventional coefficient (r(2)) of 0.636 and 0.986, respectively. Both models were validated by an external test set of eight compounds and gave satisfactory prediction (r(pred)(2)) of 0.772 and 0.701 for CoMFA and CoMSIA models, respectively. This pharmacophore based 3D-QSAR approach provides significant insights that can be used to design novel, potent and selective SHE inhibitors. PMID:22546667

  11. 3D-Pharmacophore Identification for κ-Opioid Agonists Using Ligand-Based Drug-Design Techniques

    NASA Astrophysics Data System (ADS)

    Yamaotsu, Noriyuki; Hirono, Shuichi

    A selective κ-opioid receptor (KOR) agonist might act as a powerful analgesic without the side effects of μ-opioid receptor-selective drugs such as morphine. The eight classes of known KOR agonists have different chemical structures, making it difficult to construct a pharmacophore model that takes them all into account. Here, we summarize previous efforts to identify the pharmacophore for κ-opioid agonists and propose a new three-dimensional pharmacophore model that encompasses the κ-activities of all classes. This utilizes conformational sampling of agonists by high-temperature molecular dynamics and pharmacophore extraction through a series of molecular superpositions.

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

    PubMed

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

    2004-01-01

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

  13. Ligand based validated comparative chemometric modeling and pharmacophore mapping of aurone derivatives as antimalarial agents.

    PubMed

    Adhikari, Nilanjan; Halder, Amit Kumar; Mondal, Chanchal; Jha, Tarun

    2013-09-01

    Chloroquine resistance is nowadays a great problem. Aurone derivatives are effective against chloroquine resistant parasite. Ligand based validated comparative chemometric modeling through 2D-QSAR and kNN-MFA 3DQSAR studies as well as common feature 3D pharmacophore mapping were done on thirtyfive aurone derivatives having antimalarial activity. Statistically significant 2D-QSAR models were generated on unsplitted as well as splitted dataset by MLR and PLS technique. The MLR model of the unsplitted method was validated by two-deep cross validation and 10 fold cross validation for determining the predictive ability. The PLS technique of the unsplitted method was done to compare the significance of these methods. In the splitted method, model was developed on the training set by Y-based ranking method by using the same descriptors and was validated on fifty pairs of the test and the training sets by k-MCA technique. These models generated by using the same descriptors were well validated irrespective of MLR as well as PLS analysis of unsplitted as well as splitted methods and are showing similar results. Therefore, these descriptors and model generated were reliable and robust. The kNN-MFA 3D-QSAR models were generated by three variable selection methods: genetic algorithm, simulated annealing and stepwise regression. The kNN-MFA 3D-QSAR results support the 2D QSAR data and in turn validate the earlier observed SAR results. Common feature 3D-pharmacophore generation was performed on these compounds to validate both 2D and 3D-QSAR studies as well as the earlier observed SAR data. The work highlights the required structural features for the higher antimalarial activity. PMID:24010937

  14. Structural requirements for potential HIV-integrase inhibitors identified using pharmacophore-based virtual screening and molecular dynamics studies.

    PubMed

    Islam, Md Ataul; Pillay, Tahir S

    2016-02-23

    Acquired immunodeficiency syndrome (AIDS) is a life-threatening disease which is a collection of symptoms and infections caused by a retrovirus, human immunodeficiency virus (HIV). There is currently no curative treatment and therapy is reliant on the use of existing anti-retroviral drugs. Pharmacoinformatics approaches have already proven their pivotal role in the pharmaceutical industry for lead identification and optimization. In the current study, we analysed the binding preferences and inhibitory activity of HIV-integrase inhibitors using pharmacoinformatics. A set of 30 compounds were selected as the training set of a total 540 molecules for pharmacophore model generation. The final model was validated by statistical parameters and further used for virtual screening. The best mapped model (R = 0.940, RMSD = 2.847, Q(2) = 0.912, se = 0.498, Rpred(2) = 0.847 and rm(test)(2) = 0.636) explained that two hydrogen bond acceptor and one aromatic ring features were crucial for the inhibition of HIV-integrase. From virtual screening, initial hits were sorted using a number of parameters and finally two compounds were proposed as promising HIV-integrase inhibitors. Drug-likeness properties of the final screened compounds were compared to FDA approved HIV-integrase inhibitors. HIV-integrase structure in complex with the most active and final screened compounds were subjected to 50 ns molecular dynamics (MD) simulation studies to check comparative stability of the complexes. The study suggested that the screened compounds might be promising HIV-integrase inhibitors. The new chemical entities obtained from the NCI database will be subjected to experimental studies to confirm potential inhibition of HIV integrase. PMID:26809073

  15. Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

    PubMed Central

    Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P.; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh

    2015-01-01

    Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC50 in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10−6 cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice. PMID:26517557

  16. Pharmacophore modeling using Site-Identification by Ligand Competitive Saturation (SILCS) with multiple probe molecules

    PubMed Central

    Yu, Wenbo; Lakkaraju, Sirish Kaushik; Raman, E. Prabhu; Fang, Lei; MacKerell, Alexander D.

    2015-01-01

    Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues as SILCS naturally takes both protein flexibility and desolvation effects into account by using full MD simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, re-ranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design. PMID:25622696

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

    PubMed

    Mitra, Indrani; Saha, Achintya; Roy, Kunal

    2013-03-01

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

  18. Molecular modelling on small molecular CDK2 inhibitors: an integrated approach using a combination of molecular docking, 3D-QSAR and pharmacophore modelling.

    PubMed

    Yuan, H; Liu, H; Tai, W; Wang, F; Zhang, Y; Yao, S; Ran, T; Lu, S; Ke, Z; Xiong, X; Xu, J; Chen, Y; Lu, T

    2013-10-01

    Cyclin-dependent kinase 2 (CDK2) has been identified as an important target for developing novel anticancer agents. Molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and pharmacophore modelling were combined with the ultimate goal of studying the structure-activity relationship of CDK2 inhibitors. The comparative molecular similarity indices analysis (CoMSIA) model constructed based on a set of 3-aminopyrazole derivatives as CDK2 inhibitors gave statistically significant results (q (2) = 0.700; r (2) = 0.982). A HypoGen pharmacophore model, constructed using diverse CDK2 inhibitors, also showed significant statistics ([Formula: see text]Cost = 61.483; RMSD = 0.53; Correlation coefficient = 0.98). The small residues and error values between the estimated and experimental activities of the training and test set compounds proved their strong capability of activity prediction. The structural insights obtained from these two models were consistent with each other. The pharmacophore model summarized the important pharmacophoric features required for protein-ligand binding. The 3D contour maps in combination with the comprehensive pharmacophoric features helped to better interpret the structure-activity relationship. The results will be beneficial for the discovery and design of novel CDK2 inhibitors. The simplicity of this approach provides expansion to its applicability in optimizing other classes of small molecular CDK2 inhibitors. PMID:23941641

  19. Structure Based Design, Synthesis, Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Novel Cyclophilin D Inhibitors

    PubMed Central

    2015-01-01

    Cyclophilin D (CypD) is a peptidyl prolyl isomerase F that resides in the mitochondrial matrix and associates with the inner mitochondrial membrane during the mitochondrial membrane permeability transition. CypD plays a central role in opening the mitochondrial membrane permeability transition pore (mPTP) leading to cell death and has been linked to Alzheimer’s disease (AD). Because CypD interacts with amyloid beta (Aβ) to exacerbate mitochondrial and neuronal stress, it is a potential target for drugs to treat AD. Since appropriately designed small organic molecules might bind to CypD and block its interaction with Aβ, 20 trial compounds were designed using known procedures that started with fundamental pyrimidine and sulfonamide scaffolds know to have useful therapeutic effects. Two-dimensional (2D) quantitative structure–activity relationship (QSAR) methods were applied to 40 compounds with known IC50 values. These formed a training set and were followed by a trial set of 20 designed compounds. A correlation analysis was carried out comparing the statistics of the measured IC50 with predicted values for both sets. Selectivity-determining descriptors were interpreted graphically in terms of principle component analyses. These descriptors can be very useful for predicting activity enhancement for lead compounds. A 3D pharmacophore model was also created. Molecular dynamics simulations were carried out for the 20 trial compounds with known IC50 values, and molecular descriptors were determined by 2D QSAR studies using the Lipinski rule-of-five. Fifteen of the 20 molecules satisfied all 5 Lipinski rules, and the remaining 5 satisfied 4 of the 5 Lipinski criteria and nearly satisfied the fifth. Our previous use of 2D QSAR, 3D pharmacophore models, and molecular docking experiments to successfully predict activity indicates that this can be a very powerful technique for screening large numbers of new compounds as active drug candidates. These studies will

  20. First Chemical Feature Based Pharmacophore Modeling of Potent Retinoidal Retinoic Acid Metabolism Blocking Agents (RAMBAs): Identification of Novel RAMBA Scaffolds

    PubMed Central

    Purushottamachar, Puranik; Patel, Jyoti B.; Gediya, Lalji K; Clement, Omoshile O.; Njar, Vincent C. O.

    2011-01-01

    The first three-dimensional (3D) pharmacophore model was developed for potent retinoidal retinoic acid metabolism blocking agents (RAMBAs) with IC50 values ranging from 0.0009 to 5.84 nM. The seven common chemical features in these RAMBAs as deduced by the Catalyst/HipHop program include five hydrophobic groups (hydrophobes), one hydrogen bond acceptor (HBA) and one ring aromatic group. Using the pharmacophore model as a 3D search query against NCI and Maybridge conformational Catalyst formatted databases; we retrieved several compounds with different structures (scaffolds) as hits. Twenty one retrieved hits were tested for RAMBA activity at 100 nM concentration. The most potent of these compounds, NCI10308597 and HTS01914 showed inhibitory potencies less (54.7% and 53.2%, respectively, at 100 nM) than those of our best previously reported RAMBAs VN/12-1 and VN/14-1 (90% and 86%, respectively, at 100 nM). Docking studies using a CYP26A1 homology model revealed that our most potent RAMBAs showed similar binding to the one observed for a series of RAMBAs reported previously by others. Our data shows the potential of our pharmacophore model in identifying structurally diverse and potent RAMBAs. Further refinement of the model and searches of other robust databases is currently in progress with a view to identifying and optimizing new leads. PMID:22130607

  1. Combinatorial Pharmacophore Modeling of Multidrug and Toxin Extrusion Transporter 1 Inhibitors: a Theoretical Perspective for Understanding Multiple Inhibitory Mechanisms

    PubMed Central

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

    2015-01-01

    A combinatorial pharmacophore (CP) model for Multidrug and toxin extrusion 1 (MATE1/SLC47A1) inhibitors was developed based on a data set including 881 compounds. The CP model comprises four individual pharmacophore hypotheses, HHR1, DRR, HHR2 and AAAP, which can successfully identify the MATE1 inhibitors with an overall accuracy around 75%. The model emphasizes the importance of aromatic ring and hydrophobicity as two important structural determinants for MATE1 inhibition. Compared with the pharmacophore model of Organic Cation Transporter 2 (OCT2/ SLC22A2), a functional related transporter of MATE1, the hypotheses of AAAP and PRR5 are suggested to be responsible for their ligand selectivity, while HHR a common recognition pattern for their dual inhibition. A series of analysis including molecular sizes of inhibitors matching different hypotheses, matching of representative MATE1 inhibitors and molecular docking indicated that the small inhibitors matching HHR1 and DRR involve in competitive inhibition, while the relatively large inhibitors matching AAAP are responsible for the noncompetitive inhibition by locking the conformation changing of MATE1. In light of the results, a hypothetical model for inhibiting transporting mediated by MATE1 was proposed. PMID:26330298

  2. Pharmacophore modeling study based on known spleen tyrosine kinase inhibitors together with virtual screening for identifying novel inhibitors.

    PubMed

    Xie, Huan-Zhang; Li, Lin-Li; Ren, Ji-Xia; Zou, Jun; Yang, Li; Wei, Yu-Quan; Yang, Sheng-Yong

    2009-04-01

    In this investigation, chemical features based 3D pharmacophore models were developed based on the known inhibitors of Spleen tyrosine kinase (Syk) with the aid of hiphop and hyporefine modules within catalyst. The best quantitative pharmacophore model, Hypo1, was used as a 3D structural query for retrieving potential inhibitors from chemical databases including Specs, NCI, MayBridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies to refine the retrieved hits. Finally 30 compounds were selected from the top ranked hit compounds and conducted an in vitro kinase inhibitory assay. Six compounds showed a good inhibitory potency against Syk, which have been selected for further investigation. PMID:19254842

  3. 3D-pharmacophore models for selective A2A and A2B adenosine receptor antagonists.

    PubMed

    Wei, Jing; Wang, Songqing; Gao, Shaofen; Dai, Xuedong; Gao, Qingzhi

    2007-01-01

    Three-dimensional pharmacophore models were generated for A2A and A2B adenosine receptors (ARs) based on highly selective A2A and A2B antagonists using the Catalyst program. The best pharmacophore model for selective A2A antagonists (Hypo-A2A) was obtained through a careful validation process. Four features contained in Hypo-A2A (one ring aromatic feature (R), one positively ionizable feature (P), one hydrogen bond acceptor lipid feature (L), and one hydrophobic feature (H)) seem to be essential for antagonists in terms of binding activity and A2A AR selectivity. The best pharmacophore model for selective A2B antagonists (Hypo-A2B) was elaborated by modifying the Catalyst common features (HipHop) hypotheses generated from the selective A2B antagonists training set. Hypo-A2B also consists of four features: one ring aromatic feature (R), one hydrophobic aliphatic feature (Z), and two hydrogen bond acceptor lipid features (L). All features play an important role in A2B AR binding affinity and are essential for A2B selectivity. Both A2A and A2B pharmacophore models have been validated toward a wide set of test molecules containing structurally diverse selective antagonists of all AR subtypes. They are capable of identifying correspondingly high potent antagonists and differentiating antagonists between subtypes. The results of our study will act as a valuable tool for retrieving structurally diverse compounds with desired biological activities and designing novel selective adenosine receptor ligands. PMID:17330954

  4. The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies

    PubMed Central

    2011-01-01

    Background Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. Methods In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. Results The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high Güner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from Aβ toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. Conclusions The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites. PMID:21251245

  5. A Teach-Discover-Treat Application of ZincPharmer: An Online Interactive Pharmacophore Modeling and Virtual Screening Tool

    PubMed Central

    Koes, David Ryan; Pabon, Nicolas A.; Deng, Xiaoyi; Phillips, Margaret A.; Camacho, Carlos J.

    2015-01-01

    The 2012 Teach-Discover-Treat (TDT) community-wide experiment provided a unique opportunity to test prospective virtual screening protocols targeting the anti-malarial target dihydroorotate dehydrogenase (DHODH). Facilitated by ZincPharmer, an open access online interactive pharmacophore search of the ZINC database, the experience resulted in the development of a novel classification scheme that successfully predicted the bound structure of a non-triazolopyrimidine inhibitor, as well as an overall hit rate of 27% of tested active compounds from multiple novel chemical scaffolds. The general approach entailed exhaustively building and screening sparse pharmacophore models comprising of a minimum of three features for each bound ligand in all available DHODH co-crystals and iteratively adding features that increased the number of known binders returned by the query. Collectively, the TDT experiment provided a unique opportunity to teach computational methods of drug discovery, develop innovative methodologies and prospectively discover new compounds active against DHODH. PMID:26258606

  6. Search for Potent and Selective Aurora A Inhibitors Based on General Ser/Thr Kinase Pharmacophore Model

    PubMed Central

    Vasilevich, Natalya I.; Tatarskiy, Victor V.; Aksenova, Elena A.; Kazyulkin, Denis N.; Afanasyev, Ilya I.

    2016-01-01

    Based on the data for compounds known from the literature to be active against various types of Ser/Thr kinases, a general pharmachophore model for these types of kinases was developed. The search for the molecules fitting to this pharmacophore among the ASINEX proprietary library revealed a number of compounds, which were tested and appeared to possess some activity against Ser/Thr kinases such as Aurora A, Aurora B and Haspin. Our work on the optimization of these molecules against Aurora A kinase allowed us to achieve several hits in a 3–5 nM range of activity with rather good selectivity and Absorption, Distribution, Metabolism, and Excretion (ADME) properties, and cytotoxicity against 16 cancer cell lines. Thus, we showed the possibility to fine-tune the general Ser/Thr pharmacophore to design active and selective compounds against desired types of kinases. PMID:27089349

  7. Search for Potent and Selective Aurora A Inhibitors Based on General Ser/Thr Kinase Pharmacophore Model.

    PubMed

    Vasilevich, Natalya I; Tatarskiy, Victor V; Aksenova, Elena A; Kazyulkin, Denis N; Afanasyev, Ilya I

    2016-01-01

    Based on the data for compounds known from the literature to be active against various types of Ser/Thr kinases, a general pharmachophore model for these types of kinases was developed. The search for the molecules fitting to this pharmacophore among the ASINEX proprietary library revealed a number of compounds, which were tested and appeared to possess some activity against Ser/Thr kinases such as Aurora A, Aurora B and Haspin. Our work on the optimization of these molecules against Aurora A kinase allowed us to achieve several hits in a 3-5 nM range of activity with rather good selectivity and Absorption, Distribution, Metabolism, and Excretion (ADME) properties, and cytotoxicity against 16 cancer cell lines. Thus, we showed the possibility to fine-tune the general Ser/Thr pharmacophore to design active and selective compounds against desired types of kinases. PMID:27089349

  8. Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

    PubMed Central

    Wang, Yen-Ling

    2014-01-01

    Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (rtest) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

  9. 4D-QSAR analysis and pharmacophore modeling: electron conformational-genetic algorithm approach for penicillins.

    PubMed

    Yanmaz, Ersin; Sarıpınar, Emin; Şahin, Kader; Geçen, Nazmiye; Çopur, Fatih

    2011-04-01

    4D-QSAR studies were performed on a series of 87 penicillin analogues using the electron conformational-genetic algorithm (EC-GA) method. In this EC-based method, each conformation of the molecular system is described by a matrix (ECMC) with both electron structural parameters and interatomic distances as matrix elements. Multiple comparisons of these matrices within given tolerances for high active and low active penicillin compounds allow one to separate a smaller number of matrix elements (ECSA) which represent the pharmacophore groups. The effect of conformations was investigated building model 1 and 2 based on ensemble of conformers and single conformer, respectively. GA was used to select the most important descriptors and to predict the theoretical activity of the training (74 compounds) and test (13 compounds, commercial penicillins) sets. The model 1 for training and test sets obtained by optimum 12 parameters gave more satisfactory results (R(training)(2)=0.861, SE(training)=0.044, R(test)(2)=0.892, SE(test)=0.099, q(2)=0.702, q(ext1)(2)=0.777 and q(ext2)(2)=0.733) than model 2 (R(training)(2)=0.774, SE(training)=0.056, R(test)(2)=0.840, SE(test)=0.121, q(2)=0.514, q(ext1)(2)=0.641 and q(ext2)(2)=0.570). To estimate the individual influence of each of the molecular descriptors on biological activity, the E statistics technique was applied to the derived EC-GA model. PMID:21419636

  10. Design of e-pharmacophore models using compound fragments for the trans-sialidase of Trypanosoma cruzi: screening for novel inhibitor scaffolds

    PubMed Central

    Miller, Bill R.; Roitberg, Adrian E.

    2013-01-01

    Chagas’ is a fatal disease that affects millions of people worldwide. The lack of safe and effective treatments for Chagas’ highlights the need for the discovery of new drugs to fight the disease. Trypanosoma cruzi, the parasitic cause of Chagas’ disease, synthesizes a trans-sialidase (TcTS) enzyme responsible for the transfer of sialic acids from the host cell surface to glycoconjugates on the parasitic cell surface. TcTS has no human analogs and is vital to the life cycle of T. cruzi, making TcTS an important enzyme for drug design against Chagas’ disease. We use fragment docking to generate various e-pharmacophore hypotheses depicting protein residues important for ligand binding. Virtual screening of the ZINC Clean Leads database with more than 4 million compounds using the e-pharmacophore models found 82 potential inhibitors of TcTS. Molecular dynamics and free energy of binding calculations were used to rank the compounds based on their affinity for TcTS. Two compounds—ZINC13359679 and ZINC02576132—were found to be the most promising lead candidates for TcTS inhibition, and their binding modes are analyzed in detail. PMID:24012872

  11. Enolate-Forming Phloretin Pharmacophores: Hepatoprotection in an Experimental Model of Drug-Induced Toxicity.

    PubMed

    Geohagen, Brian C; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence; LoPachin, Richard M

    2016-06-01

    Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2',4',6'-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. PMID:27029584

  12. Discovery of new human epidermal growth factor receptor-2 (HER2) inhibitors for potential use as anticancer agents via ligand-based pharmacophore modeling.

    PubMed

    Zalloum, Hiba; Tayyem, Rabab; Irmaileh, Basha'er Abu-; Bustanji, Yasser; Zihlif, Malek; Mohammad, Mohammad; Rjai, Talal Abu; Mubarak, Mohammad S

    2015-09-01

    To discover potential antitumor agents directed toward human epidermal growth factor receptor-2HER2/ErbB2 overexpression in cancer, we have explored the pharmacophoric space of 115 HER2/ErbB2 inhibitors. This identified 240 pharmacophores which were subsequently clustered into 20 groups and cluster centers were used as 3D-pharmacophoric descriptors in QSAR analysis with 2D-physicochemical descriptors to select the optimal combination. We were obliged to use ligand efficiency as the response variable because the logarithmic transformation of bioactivities failed to access self-consistent QSAR models. Two binding pharmacophore models emerged in the optimal QSAR equation, suggesting the existence of distinct binding modes accessible to ligands within the HER2/ErbB2 binding pocket. The QSAR equation and its associated pharmacophore models were employed to screen the National Cancer Institute (NCI) and Drug Bank databases to search for new, promising, and structurally diverse HER2 inhibitory leads. Inhibitory activities were tested against HER2-overexpressing SKOV3 Ovarian cancer cell line and MCF-7 which express low levels of HER2. In silico mining identified 80 inhibitors out of which four HER2 selective compounds inhibited the growth of SKOV3 cells with IC50 values < 5μM and with virtually no effect in MCF-7 cells. These lead compounds are excellent candidates for further optimization. PMID:26188796

  13. Discovery of non-oxime reactivators using an in silico pharmacophore model of oxime reactivators of OP-inhibited acetylcholinesterase.

    PubMed

    Bhattacharjee, Apurba K; Marek, Elizabeth; Le, Ha Thu; Gordon, Richard K

    2012-03-01

    We earlier reported an in silico pharmacophore model for reactivation of oximes to tabun-inhibited AChE. Since DFP (diisopropylfluorophosphate) like tabun is a G-agent simulator, we utilized the model as a rational strategy to discover non-oxime reactivators of DFP-inhibited AChE in this study. The phramacophore was used for virtual screening of two commercial databases, Maybridge and ChemNavigator, to identify reactivators which lack the oxime functions. The procedure led us to identify several potent non-oxime compounds that reactivate DFP-inhibited AChE. These non-oxime reactivators contain a nucleophile group in lieu of the oxime moiety in the compound. Five of these novel non-oximes showed Kr values within ten-fold of 2-PAM in an in vitro assay. The pharmacophore model contained a hydrogen bond acceptor, a hydrogen bond donor, and an aromatic ring features distributed in a 3D space. Calculated stereoelectronic properties reported earlier with respect to the location of molecular orbitals and electrostatic potentials were consistent with the model and the newly identified compounds. Down selection of compounds after virtual screening was performed on the basis of fit score to the model, conformational energy, and in silico evaluations for favorable blood-brain barrier (BBB) penetrability, octanol-water partition (log P), and toxicity (rat oral LD(50)) assessments. In vitro reactivation efficacy of the compounds was evaluated in a DFP-inhibited eel acetylcholinesterase assay. PMID:22309910

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

    PubMed

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

    2016-07-25

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

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

    PubMed

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

    2016-01-01

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

  16. Peptide inhibitors of botulinum neurotoxin serotype A: design, inhibition, cocrystal structures, structure-activity relationship and pharmacophore modeling

    SciTech Connect

    Kumar G.; Swaminathan S.; Kumaran, D.; Ahmed, S. A.

    2012-05-01

    Clostridium botulinum neurotoxins are classified as Category A bioterrorism agents by the Centers for Disease Control and Prevention (CDC). The seven serotypes (A-G) of the botulinum neurotoxin, the causative agent of the disease botulism, block neurotransmitter release by specifically cleaving one of the three SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins and induce flaccid paralysis. Using a structure-based drug-design approach, a number of peptide inhibitors were designed and their inhibitory activity against botulinum serotype A (BoNT/A) protease was determined. The most potent peptide, RRGF, inhibited BoNT/A protease with an IC{sub 50} of 0.9 {micro}M and a K{sub i} of 358 nM. High-resolution crystal structures of various peptide inhibitors in complex with the BoNT/A protease domain were also determined. Based on the inhibitory activities and the atomic interactions deduced from the cocrystal structures, the structure-activity relationship was analyzed and a pharmacophore model was developed. Unlike the currently available models, this pharmacophore model is based on a number of enzyme-inhibitor peptide cocrystal structures and improved the existing models significantly, incorporating new features.

  17. Pharmacophore modeling and atom-based 3D-QSAR studies on amino derivatives of indole as potent isoprenylcysteine carboxyl methyltransferase (Icmt) inhibitors

    NASA Astrophysics Data System (ADS)

    Bhadoriya, Kamlendra Singh; Sharma, Mukesh C.; Jain, Shailesh V.

    2015-02-01

    Icmt enzymes are of particular importance in the post-translational modification of proteins that are involved in the regulation of cell growth. Thus, effective Icmt inhibitors may be of significant therapeutic importance in oncogenesis. To determine the structural requirements responsible for high affinity of previously reported amino derivatives of indole as Icmt inhibitors, a successful pharmacophore generation and atom-based 3D-QSAR analysis have been carried out. The best four-point pharmacophore model with four features HHRR: two hydrophobic groups (H) and two aromatic rings (R) as pharmacophore features was developed by PHASE module of Schrodinger suite. In this study, highly predictive 3D-QSAR models have been developed for Icmt inhibition using HHRR.191 hypothesis. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least-square (PLS) statistics results. The validation of the PHASE model was done by dividing the dataset into training and test set. The statistically significant the four-point pharmacophore hypothesis yielded a 3D-QSAR model with good PLS statistics results (R2 = 0.9387, Q2 = 0.8132, F = 114.8, SD = 0.1567, RMSE = 0.2682, Pearson-R = 0.9147). The generated model showed excellent predictive power, with a correlation coefficient of Q2 = 0.8132. The results of ligand-based pharmacophore hypothesis and atom-based 3D-QSAR provide detailed structural insights as well as highlights important binding features of novel amino derivatives of indole as Icmt inhibitors which can afford guidance for the rational drug design of novel, potent and promising Icmt inhibitors with enhanced potencies and may prove helpful for further lead optimization and virtual screening.

  18. Binding mode analyses and pharmacophore model development for stilbene derivatives as a novel and competitive class of α-glucosidase inhibitors.

    PubMed

    Lee, Yuno; Kim, Songmi; Kim, Jun Young; Arooj, Mahreen; Kim, Siu; Hwang, Swan; Kim, Byeong-Woo; Park, Ki Hun; Lee, Keun Woo

    2014-01-01

    Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental Ki value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the Ki values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives. PMID:24465730

  19. The discovery of novel vascular endothelial growth factor receptor tyrosine kinases inhibitors: pharmacophore modeling, virtual screening and docking studies.

    PubMed

    Yu, Hui; Wang, Zhanli; Zhang, Liangren; Zhang, Jufeng; Huang, Qian

    2007-03-01

    We have applied pharmacophore generation, database searching and docking methodologies to discover new structures for the design of vascular endothelial growth factor receptors, the tyrosine kinase insert domain-containing receptor kinase inhibitors. The chemical function based pharmacophore models were built for kinase insert domain-containing receptor kinase inhibitors from a set of 10 known inhibitors using the algorithm HipHop, which is implemented in the CATALYST software. The highest scoring HipHop model consists of four features: one hydrophobic, one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic function. Using the algorithm CatShape within CATALYST, the bound conformation of 4-amino-furo [2, 3-d] pyrimidine binding to kinase insert domain-containing receptor kinase was used to generate a shape query. A merged shape and hypothesis query that is in an appropriate alignment was then built. The combined shape and hypothesis model was used as a query to search Maybridge database for other potential lead compounds. A total of 39 compounds were retrieved as hits. The hits obtained were docked into kinase insert domain-containing receptor kinase active site. One novel potential lead was proposed based on CATALYST fit value, LigandFit docking scores, and examination of how the hit retain key interactions known to be required for kinase binding. This compound inhibited vascular endothelial growth factor stimulated kinase insert domain-containing receptor phosphorylation in human umbilical vein endothelial cells. PMID:17441906

  20. Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

    PubMed

    Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

    2013-10-28

    Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization. PMID:24050442

  1. 3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors

    PubMed Central

    Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong Keun; Lee, Keun Woo

    2011-01-01

    Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC50) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors. PMID:22272131

  2. Pharmacophore modeling, virtual screening, molecular docking studies and density functional theory approaches to identify novel ketohexokinase (KHK) inhibitors.

    PubMed

    Kavitha, Rengarajan; Karunagaran, Subramanian; Chandrabose, Subramaniam Subhash; Lee, Keun Woo; Meganathan, Chandrasekaran

    2015-12-01

    Fructose catabolism starts with phosphorylation of d-fructose to fructose 1-phosphate, which is performed by ketohexokinase (KHK). Fructose metabolism may be the key to understand the long-term consumption of fructose in human's obesity, diabetes and metabolic states in western populations. The inhibition of KHK has medicinally potential roles in fructose metabolism and the metabolic syndrome. To identify the essential chemical features for KHK inhibition, a three-dimensional (3D) chemical-feature-based QSAR pharmacophore model was developed for the first time by using Discovery Studio v2.5 (DS). The best pharmacophore hypothesis (Hypo1) consisting two hydrogen bond donor, two hydrophobic features and has exhibited high correlation co-efficient (0.97), cost difference (76.1) and low RMS (0.66) value. The robustness and predictability of Hypo1 was validated by fisher's randomization method, test set, and the decoy set. Subsequently, chemical databases like NCI, Chembridge and Maybridge were screened for validated Hypo1. The screened compounds were further analyzed by applying drug-like filters such as Lipinski's rule of five, ADME properties, and molecular docking studies. Further, the highest occupied molecular orbital, lowest unoccupied molecular orbital and energy gap values were calculated for the hits compounds using density functional theory. Finally, 3 hit compounds were selected based on their good molecular interactions with key amino acids in the KHK active site, GOLD fitness score, and lowest energy gaps. PMID:26521124

  3. Virtual screening based on pharmacophore model followed by docking simulation studies in search of potential inhibitors for p38 map kinase.

    PubMed

    Shahlaei, Mohsen; Doosti, Elham

    2016-05-01

    P38 mitogen-activated protein (MAP) kinase inhibitors are closely involved in the production of inflammatory cytokines. These compounds are considered promising therapeutic agents for chronic inflammatory disorders. In this study, a ligand-based pharmacophore model of p38 map kinase inhibitors was developed. The best five features pharmacophore model includes two hydrogen bond acceptors, two hydrophobic and an aromatic hydrophobic features, which has the highest correlation coefficient (0.822), cost difference (134.158), low root mean square (RMS) of error (1.315). As well as the developed model shows a high goodness of fit and enrichment factor. The pharmacophore hypothesis has been validated by using a series of similar structures with varying affinities for the p38 map kinase. It also has been employed as a search query in different database searching with the ultimate goal of finding novel compounds which have the possibility to be modified into novel lead molecules. As a result, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. The results from pharmacophore modeling and molecular docking are complementary to each other and could serve as a useful approach for the discovery of potent small molecules as p38 map kinase inhibitors. PMID:27133076

  4. Synthesis and pharmacophore modeling of novel quinazolines bearing a biologically active sulfonamide moiety.

    PubMed

    Ghorab, Mostafa M; Ismail, Zienab H; Radwan, Awwad A; Abdalla, Mohamad

    2013-03-01

    In the present work, interaction of the strategic starting material, methyl 2-isothiocyanatobenzoate (1), with sulfa drugs resulted in the formation of methyl 2-[3-(4-(N-substituted sulfamoyl)phenyl)thioureido] benzoates 2-5, which upon reaction with hydrazine hydrate afforded N-amino derivatives 6-9. Triazoloquinazoline derivatives 10-18 were obtained via reaction of compounds 6-8 with aromatic aldehydes. Also, the reaction of compound 8 with formic acid gave the corresponding triazoloquinazoline derivative 19. Triazinoquinazoline derivatives 22, 23 were obtained via reaction of N-amino derivatives 6 or 8 with ethyl chloroacetate. Interaction of 6 with diethyloxalate yielded triazoloquinazoline 26. The synthesized compounds were screened for their in vitro antimicrobial activities and some of them exhibited promising antibacterial activity compared to ampicillin as positive control. Compounds that revealed significant activity are able to satisfy effectively the proposed pharmacophore geometry. PMID:23482309

  5. Small molecule non-peptide inhibitors of botulinum neurotoxin serotype E: Structure-activity relationship and a pharmacophore model.

    PubMed

    Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

    2016-09-15

    Botulinum neurotoxins (BoNTs) are the most poisonous biological substance known to humans. They cause flaccid paralysis by blocking the release of acetylcholine at the neuromuscular junction. Here, we report a number of small molecule non-peptide inhibitors of BoNT serotype E. The structure-activity relationship and a pharmacophore model are presented. Although non-peptidic in nature, these inhibitors mimic key features of the uncleavable substrate peptide Arg-Ile-Met-Glu (RIME) of the SNAP-25 protein. Among the compounds tested, most of the potent inhibitors bear a zinc-chelating moiety connected to a hydrophobic and aromatic moiety through a carboxyl or amide linker. All of them show low micromolar IC50 values. PMID:27353886

  6. Discovery of non-oxime reactivators using an in silico pharmacophore model of reactivators for DFP-inhibited acetylcholinesterase.

    PubMed

    Bhattacharjee, Apurba K; Marek, Elizabeth; Le, Ha Thu; Ratcliffe, Ruthie; DeMar, James C; Pervitsky, Dmitry; Gordon, Richard K

    2015-01-27

    Utilizing our previously reported in silico pharmacophore model for reactivation efficacy of oximes, we present here a discovery of twelve new non-oxime reactivators of diisopropylfluorophosphate (DFP)-inhibited acetylcholinesterase (AChE) obtained through virtual screening of an in-house compound database. Rate constant (kr) efficacy values of the non-oximes were found to be within ten-fold of pralidoxime (2-PAM) in an in vitro DFP inhibited eel AChE assay and one of them showed in vivo efficacy comparable to 2-PAM against brain symptoms for DFP induced neuropathology in guinea pigs. Short listing of the identified compounds were performed on the basis of in silico evaluations for favorable blood brain barrier penetrability, octanol-water partition (Clog P), toxicity (rat oral LD50) and binding affinity to the active site of the crystal structure of a OP- inhibited AChE. PMID:25461321

  7. Local intersection volume: a new 3D descriptor applied to develop a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands.

    PubMed

    Verli, Hugo; Albuquerque, Magaly Girão; Bicca de Alencastro, Ricardo; Barreiro, Eliezer J

    2002-03-01

    In this work, we have developed a new descriptor, named local intersection volume (LIV), in order to compose a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands. The LIV can be classified as a 3D local shape descriptor in contraposition to the global shape descriptors. We have selected from the literature 49 non-benzodiazepine compounds as a training data set and the model was obtained and evaluated by genetic algorithms (GA) and partial least-squares (PLS) methods using LIVs as descriptors. The LIV 3D-QSAR model has a good predictive capacity according the cross-validation test by "leave-one-out" procedure (Q(2)=0.72). The developed model was compared to a comprehensive and extensive SAR pharmacophore model, recently proposed by Cook and co-workers, for benzodiazepine receptor ligands [J. Med. Chem. 43 (2000) 71]. It showed a relevant correlation with the pharmacophore groups pointed out in that work. Our LIV 3D-QSAR model was also able to predict affinity values for a series of nine compounds (test data set) that was not included into the training data set. PMID:11900866

  8. First chemical feature-based pharmacophore modeling of potent retinoidal retinoic acid metabolism blocking agents (RAMBAs): identification of novel RAMBA scaffolds.

    PubMed

    Purushottamachar, Puranik; Patel, Jyoti B; Gediya, Lalji K; Clement, Omoshile O; Njar, Vincent C O

    2012-01-01

    The first three-dimensional (3D) pharmacophore model was developed for potent retinoidal retinoic acid metabolism blocking agents (RAMBAs) with IC(50) values ranging from 0.0009 to 5.84nM. The seven common chemical features in these RAMBAs as deduced by the Catalyst/HipHop program include five hydrophobic groups (hydrophobes), and two hydrogen bond acceptors. Using the pharmacophore model as a 3D search query against NCI and Maybridge conformational Catalyst formatted databases; we retrieved several compounds with different structures (scaffolds) as hits. Twenty-one retrieved hits were tested for RAMBA activity at 100nM concentration. The most potent of these compounds, NCI10308597 and HTS01914 showed inhibitory potencies less (54.7% and 53.2%, respectively, at 100nM) than those of our best previously reported RAMBAs VN/12-1 and VN/14-1 (90% and 86%, respectively, at 100nM). Docking studies using a CYP26A1 homology model revealed that our most potent RAMBAs showed similar binding to the one observed for a series of RAMBAs reported previously by others. Our data shows the potential of our pharmacophore model in identifying structurally diverse and potent RAMBAs. Further refinement of the model and searches of other robust databases is currently in progress with a view to identifying and optimizing new leads. PMID:22130607

  9. A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP.

    PubMed

    Patel, Yogendra; Gillet, Valerie J; Bravi, Gianpaolo; Leach, Andrew R

    2002-01-01

    Three commercially available pharmacophore generation programs, Catalyst/HipHop, DISCO and GASP, were compared on their ability to generate known pharmacophores deduced from protein-ligand complexes extracted from the Protein Data Bank. Five different protein families were included Thrombin, Cyclin Dependent Kinase 2, Dihydrofolate Reductase, HIV Reverse Transcriptase and Thermolysin. Target pharmacophores were defined through visual analysis of the data sets. The pharmacophore models produced were evaluated qualitatively through visual inspection and according to their ability to generate the target pharmacophores. Our results show that GASP and Catalyst outperformed DISCO at reproducing the five target pharmacophores. PMID:12602956

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

    PubMed

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

    2011-01-01

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

  11. Pharmacophore Modeling and Virtual Screening for Novel Acidic Inhibitors of Microsomal Prostaglandin E2 Synthase-1 (mPGES-1)

    PubMed Central

    2011-01-01

    Microsomal prostaglandin E2 synthase-1 (mPGES-1) catalyzes prostaglandin E2 formation and is considered as a potential anti-inflammatory pharmacological target. To identify novel chemical scaffolds active on this enzyme, two pharmacophore models for acidic mPGES-1 inhibitors were developed and theoretically validated using information on mPGES-1 inhibitors from literature. The models were used to screen chemical databases supplied from the National Cancer Institute (NCI) and the Specs. Out of 29 compounds selected for biological evaluation, nine chemically diverse compounds caused concentration-dependent inhibition of mPGES-1 activity in a cell-free assay with IC50 values between 0.4 and 7.9 μM, respectively. Further pharmacological characterization revealed that also 5-lipoxygenase (5-LO) was inhibited by most of these active compounds in cell-free and cell-based assays with IC50 values in the low micromolar range. Together, nine novel chemical scaffolds inhibiting mPGES-1 are presented that may possess anti-inflammatory properties based on the interference with eicosanoid biosynthesis. PMID:21466167

  12. Identification of novel inhibitors of the steroid sulfate carrier 'sodium-dependent organic anion transporter' SOAT (SLC10A6) by pharmacophore modelling.

    PubMed

    Grosser, Gary; Baringhaus, Karl-Heinz; Döring, Barbara; Kramer, Werner; Petzinger, Ernst; Geyer, Joachim

    2016-06-15

    The sodium-dependent organic anion transporter SOAT specifically transports sulfated steroid hormones and is supposed to play a role in testicular steroid regulation and male fertility. The present study aimed to identify novel specific SOAT inhibitors for further in vitro and in vivo studies on SOAT function. More than 100 compounds of different molecular structures were screened for inhibition of the SOAT-mediated transport of dehydroepiandrosterone sulfate in stably transfected SOAT-HEK293 cells. Twenty-five of these with IC50 values covering four orders of magnitude were selected as training set for 3D pharmacophore modelling. The SOAT pharmacophore features were calculated by CATALYST and consist of three hydrophobic sites and two hydrogen bond acceptors. By substrate database screening, compound T 0511-1698 was predicted as a novel SOAT inhibitor with an IC50 of 15 μM. This value was confirmed by cell-based transport assays. Therefore, the developed SOAT pharmacophore model demonstrated its suitability in predicting novel SOAT inhibitors. PMID:27033324

  13. Ligand-Based Pharmacophore Modeling and Virtual Screening for the Discovery of Novel 17β-Hydroxysteroid Dehydrogenase 2 Inhibitors

    PubMed Central

    2014-01-01

    17β-Hydroxysteroid dehydrogenase 2 (17β-HSD2) catalyzes the inactivation of estradiol into estrone. This enzyme is expressed only in a few tissues, and therefore its inhibition is considered as a treatment option for osteoporosis to ameliorate estrogen deficiency. In this study, ligand-based pharmacophore models for 17β-HSD2 inhibitors were constructed and employed for virtual screening. From the virtual screening hits, 29 substances were evaluated in vitro for 17β-HSD2 inhibition. Seven compounds inhibited 17β-HSD2 with low micromolar IC50 values. To investigate structure–activity relationships (SAR), 30 more derivatives of the original hits were tested. The three most potent hits, 12, 22, and 15, had IC50 values of 240 nM, 1 μM, and 1.5 μM, respectively. All but 1 of the 13 identified inhibitors were selective over 17β-HSD1, the enzyme catalyzing conversion of estrone into estradiol. Three of the new, small, synthetic 17β-HSD2 inhibitors showed acceptable selectivity over other related HSDs, and six of them did not affect other HSDs. PMID:24960438

  14. Bioguided discovery and pharmacophore modeling of the mycotoxic indole diterpene alkaloids penitrems as breast cancer proliferation, migration, and invasion inhibitors

    PubMed Central

    Sallam, Asmaa A.; Houssen, Wael E.; Gissendanner, Chris R.; Orabi, Khaled Y.; Foudah, Ahmed I.; El Sayed, Khalid A.

    2013-01-01

    Marine-derived fungi have proven to be important sources of bioactive natural organohalides. The genus Penicillium is recognized as a rich source of chemically diverse bioactive secondary metabolites. This study reports the fermentation, isolation and identification of a marine-derived Penicillium species. Bioassay-guided fractionation afforded the indole diterpene alkaloids penitrems A, B, D, E and F as well as paspaline and emnidole SB (1–7). Supplementing the fermentation broth of the growing fungus with KBr afforded the new 6-bromopenitrem B (8) and the known 6-bromopenitrem E (9). These compounds showed good antiproliferative, antimigratory and anti-invasive properties against human breast cancer cells. Penitrem B also showed a good activity profile in the NCI-60 DTP human tumor cell line screen. The nematode Caenorhabditis elegans was used to assess the BK channel inhibitory activity and toxicity of select compounds. A pharmacophore model was generated to explain the structural relationships of 1–9 with respect to their antiproliferative activity against the breast cancer MCF-7 cells. The structurally less complex biosynthetic precursors, paspaline (6) and emindole SB (7), were identified as potential hits suitable for future studies. PMID:24273638

  15. Pharmacophore-Based Similarity Scoring for DOCK

    PubMed Central

    2015-01-01

    Pharmacophore modeling incorporates geometric and chemical features of known inhibitors and/or targeted binding sites to rationally identify and design new drug leads. In this study, we have encoded a three-dimensional pharmacophore matching similarity (FMS) scoring function into the structure-based design program DOCK. Validation and characterization of the method are presented through pose reproduction, crossdocking, and enrichment studies. When used alone, FMS scoring dramatically improves pose reproduction success to 93.5% (∼20% increase) and reduces sampling failures to 3.7% (∼6% drop) compared to the standard energy score (SGE) across 1043 protein–ligand complexes. The combined FMS+SGE function further improves success to 98.3%. Crossdocking experiments using FMS and FMS+SGE scoring, for six diverse protein families, similarly showed improvements in success, provided proper pharmacophore references are employed. For enrichment, incorporating pharmacophores during sampling and scoring, in most cases, also yield improved outcomes when docking and rank-ordering libraries of known actives and decoys to 15 systems. Retrospective analyses of virtual screenings to three clinical drug targets (EGFR, IGF-1R, and HIVgp41) using X-ray structures of known inhibitors as pharmacophore references are also reported, including a customized FMS scoring protocol to bias on selected regions in the reference. Overall, the results and fundamental insights gained from this study should benefit the docking community in general, particularly researchers using the new FMS method to guide computational drug discovery with DOCK. PMID:25229837

  16. Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

    PubMed Central

    Wei, Yu; Li, Jinlong; Qing, Jie; Huang, Mingjie; Wu, Ming; Gao, Fenghua; Li, Dongmei; Hong, Zhangyong; Kong, Lingbao; Huang, Weiqiang; Lin, Jianping

    2016-01-01

    The NS5B polymerase is one of the most attractive targets for developing new drugs to block Hepatitis C virus (HCV) infection. We describe the discovery of novel potent HCV NS5B polymerase inhibitors by employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods. In the RB-VS stage, after feature selection, a model with 16 descriptors was used. In the PB-VS stage, six energy-based pharmacophore (e-pharmacophore) models from different crystal structures of the NS5B polymerase with ligands binding at the palm I, thumb I and thumb II regions were used. In the DB-VS stage, the Glide SP and XP docking protocols with default parameters were employed. In the virtual screening approach, the RB-VS, PB-VS and DB-VS methods were applied in increasing order of complexity to screen the InterBioScreen database. From the final hits, we selected 5 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 5 compounds were found to inhibit NS5B polymerase with IC50 values of 2.01–23.84 μM and displayed anti-HCV activities with EC50 values ranging from 1.61 to 21.88 μM, and all compounds displayed no cellular cytotoxicity (CC50 > 100 μM) except compound N2, which displayed weak cytotoxicity with a CC50 value of 51.3 μM. The hit compound N2 had the best antiviral activity against HCV, with a selective index of 32.1. The 5 hit compounds with new scaffolds could potentially serve as NS5B polymerase inhibitors through further optimization and development. PMID:26845440

  17. Ligand-based Pharmacophore Modeling; Atom-based 3D-QSAR Analysis and Molecular Docking Studies of Phosphoinositide-Dependent Kinase-1 Inhibitors

    PubMed Central

    Kirubakaran, P.; Muthusamy, K.; Singh, K. H. D.; Nagamani, S.

    2012-01-01

    Phosphoinositide-dependent kinase-1 plays a vital role in the PI3-kinase signaling pathway that regulates gene expression, cell cycle growth and proliferation. The common human cancers include lung, breast, blood and prostate possess over stimulation of the phosphoinositide-dependent kinase-1 signaling and making phosphoinositide-dependent kinase-1 an interesting therapeutic target in oncology. A ligand-based pharmacophore and atom-based 3D-QSAR studies were carried out on a set of 82 inhibitors of PDK1. A six point pharmacophore with two hydrogen bond acceptors (A), three hydrogen bond donors (D) and one hydrophobic group (H) was obtained. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least square statistics results. The training set correlation is characterized by partial least square factors (R2 = 0.9557, SD = 0.2334, F = 215.5, P = 1.407e-32). The test set correlation is characterized by partial least square factors (Q2 ext = 0.7510, RMSE = 0.5225, Pearson-R =0.8676). The external validation indicated that our QSAR model possess high predictive power with good value of 0.99 and value of 0.88. The docking results show the binding orientations of these inhibitors at active site amino acid residues (Ala162, Thr222, Glu209 and Glu166) of phosphoinositide-dependent kinase-1 protein. The binding free energy interactions of protein-ligand complex have been calculated, which plays an important role in molecular recognition and drug design approach. PMID:23325995

  18. Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

    PubMed

    Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

    2016-01-01

    Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

  19. Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

    PubMed Central

    Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

    2016-01-01

    Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

  20. Simple but highly effective three-dimensional chemical-feature-based pharmacophore model for diketo acid derivatives as hepatitis C virus RNA-dependent RNA polymerase inhibitors.

    PubMed

    Di Santo, Roberto; Fermeglia, Maurizio; Ferrone, Marco; Paneni, Maria Silvia; Costi, Roberta; Artico, Marino; Roux, Alessandra; Gabriele, Mirko; Tardif, Keith D; Siddiqui, Aleem; Pricl, Sabrina

    2005-10-01

    A molecular modeling strategy using aryl diketo acid (ADK) derivatives recently reported in the literature as hepatitis C virus (HCV) polymerase inhibitors was designed. A 3D chemical-feature-based pharmacophore model was developed using Catalyst software, which produced 10 pharmacophore hypotheses. The top-ranked one (Hypo 1), characterized by a high correlation coefficient (r = 0.965), consisted of two hydrogen bond acceptors, one negative ionizable moiety, and two hydrophobic aromatics. This model was used to predict the anti-RNA-dependent RNA polymerase (anti-RdRp) activity of 6-(1-arylmethylpyrrol-2-yl)-1,4-dioxo-5-hexenoic acids and other ADK derivatives previously synthesized in our laboratories as HIV-1 integrase inhibitors. Furthermore, the experimental IC50 values of 9 compounds, tested in vitro against recombinant HCV polymerase, were compared with the corresponding values predicted using Hypo1. A good agreement between experimental and simulated data was obtained. The results demonstrate that the hypothesis derived in this study can be considered to be a useful tool in designing new leads based on ADK scaffolds as HCV RdRp inhibitors. PMID:16190757

  1. Identification of potential Gly/NMDA receptor antagonists by cheminformatics approach: a combination of pharmacophore modelling, virtual screening and molecular docking studies.

    PubMed

    Ugale, V G; Bari, S B

    2016-01-01

    The Gly/NMDA receptor has become known as potential target for the management of neurodegenerative diseases. Discovery of Gly/NMDA antagonists has thus attracted much attention in recent years. In the present research, a cheminformatics approach has been used to determine structural requirements for Gly/NMDA antagonism and to identify potential antagonists. Here, 37 quinoxaline derivatives were selected to develop a significant pharmacophore model with good certainty. The selected model was validated by leave-one-out cross-validation, an external test set, decoy set and Y-randomization test. Applicability domain was verified by the standardization approach. The validated 3D-QSAR model was used to screen virtual hits from the ZINC database by pharmacophore mapping. Molecular docking was used for assessment of receptor-ligand binding modes and binding affinities. The GlideScore and molecular interactions with critical amino acids were considered as crucial features to identify final hits. Furthermore, hits were analysed for in silico pharmacokinetic parameters and Lipinski's rule of five, demonstrating their potential as drug-like candidates. The PubChem and SciFinder search tools were used to authenticate the novelty of leads retrieved. Finally, five different leads have been suggested as putative novel candidates for the exploration of potent Gly/NMDA receptor antagonists. PMID:26911562

  2. Identification of Novel Inhibitors of Mycobacterium tuberculosis PknG Using Pharmacophore Based Virtual Screening, Docking, Molecular Dynamics Simulation, and Their Biological Evaluation.

    PubMed

    Singh, Nidhi; Tiwari, Sameer; Srivastava, Kishore K; Siddiqi, Mohammad Imran

    2015-06-22

    PknG is a Ser/thr protein kinase that plays a crucial role in regulatory processes within the mycobacterial cell and signaling cascade of the infected host cell. The essentiality of PknG in mycobacterial virulence by blocking phagosome-lysosome fusion as well as its role in intrinsic antibiotic resistance makes it an attractive drug target. However, only very few compounds have been reported as Mycobacterium tuberculosis PknG (MtPknG) inhibitors so far. Therefore, in an effort to find potential inhibitors against MtPknG, we report here a sequential pharmacophore-based virtual screening workflow, 3-fold docking with different search algorithms, and molecular dynamic simulations for better insight into the predicted binding mode of identified hits. After detailed analysis of the results, six ligands were selected for in vitro analysis. Three of these molecules showed significant inhibitory activity against MtPknG. In addition, inhibitory studies of mycobacterial growth in infected THP-1 macrophages demonstrated considerable growth inhibition of M. bovis BCG induced through compound NRB04248 without any cytotoxic effect against host macrophages. Our results suggest that the compound NRB04248 can be explored for further design and optimization of MtPknG inhibitors. PMID:25965448

  3. Pharmacophore-based discovery of ligands for drug transporters

    PubMed Central

    Chang, Cheng; Ekins, Sean; Bahadduri, Praveen; Swaan, Peter W.

    2006-01-01

    The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and challenges encountered with current approaches are discussed. PMID:17097188

  4. Identification of novel histone deacetylase 1 inhibitors by combined pharmacophore modeling, 3D-QSAR analysis, in silico screening and Density Functional Theory (DFT) approaches

    NASA Astrophysics Data System (ADS)

    Choubey, Sanjay K.; Mariadasse, Richard; Rajendran, Santhosh; Jeyaraman, Jeyakanthan

    2016-12-01

    Overexpression of HDAC1, a member of Class I histone deacetylase is reported to be implicated in breast cancer. Epigenetic alteration in carcinogenesis has been the thrust of research for few decades. Increased deacetylation leads to accelerated cell proliferation, cell migration, angiogenesis and invasion. HDAC1 is pronounced as the potential drug target towards the treatment of breast cancer. In this study, the biochemical potential of 6-aminonicotinamide derivatives was rationalized. Five point pharmacophore model with one hydrogen-bond acceptor (A3), two hydrogen-bond donors (D5, D6), one ring (R12) and one hydrophobic group (H8) was developed using 6-aminonicotinamide derivatives. The pharmacophore hypothesis yielded a 3D-QSAR model with correlation-coefficient (r2 = 0.977, q2 = 0.801) and it was externally validated with (r2pred = 0.929, r2cv = 0.850 and r2m = 0.856) which reveals the statistical significance of the model having high predictive power. The model was then employed as 3D search query for virtual screening against compound libraries (Zinc, Maybridge, Enamine, Asinex, Toslab, LifeChem and Specs) in order to identify novel scaffolds which can be experimentally validated to design future drug molecule. Density Functional Theory (DFT) at B3LYP/6-31G* level was employed to explore the electronic features of the ligands involved in charge transfer reaction during receptor ligand interaction. Binding free energy (ΔGbind) calculation was done using MM/GBSA which defines the affinity of ligands towards the receptor.

  5. 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.

  6. Identification of Novel BACE1 Inhibitors by Combination of Pharmacophore Modeling, Structure-Based Design and In Vitro Assay.

    PubMed

    Ju, Yuan; Li, Zicheng; Deng, Yong; Tong, Aiping; Zhou, Liangxue; Luo, Youfu

    2016-01-01

    The protease β-secretase plays a critical role in the synthesis of pathogenic amyloid-β in Alzheimer's disease. In this study, pharmacophore constructed from receptor-ligand complex was used to screen Chemdiv and Zinc database and the resulting hits were subjected to docking experiments using LiandFit and CDOCKER programs. Molecules with high consensus scores and good interaction patterns in docking programs were retained. Drug-likeness assay including Lipinski's rule of five and ADMET properties filters were further used to identify BACE1 inhibitor. Finally, 13 compounds with novel scaffolds were selected and, considering of the nature of relative high LogP value of many marketed AD drugs, three of them with top 3 predicted LogP value were evaluated for their IC50 values in vitro by BACE1 enzymatic activity study. We believe that compound 13 with an IC50 value of 136 µM can be a lead compound with great potential in BACE1 inhibition and increasing activity by subsequently structure modification or optimization. At the same time, we found that the interaction between the residues Asp228, Asp32 of BACE1 and ligands is significant through analyzing the binding mode of 13 candidate compounds. PMID:26899408

  7. A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors.

    PubMed

    Adane, Legesse; Bharatam, Prasad V; Sharma, Vikas

    2010-10-01

    A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors. PMID:19995305

  8. Protective activity of (1S,2E,4R,6R,7E,11E)-2,7,11-cembratriene-4,6-diol analogues against diisopropylfluorophosphate neurotoxicity: Preliminary structure-activity relationship and pharmacophore modeling

    PubMed Central

    Eterović, Vesna A.; Valle-Rodriguez, Angelie Del; Pérez, Dinely; Carrasco, Marimée; Khanfar, Mohammad A.; El Sayed, Khalid A.; Ferchmin, Pedro A.

    2013-01-01

    Diisopropylfluorophosphate (DFP) is an organophosphorous insecticide used as a surrogate for the more toxic chemical warfare nerve agent sarin. DFP produces neurotoxicity in vivo and irreversibly decreases the area of population spikes recorded from the CA1 region of acute hippocampal slices. (1S,2E,4R,6R,7E,11E)-2,7,11-Cembratriene-4,6-diol (1) is a neuroprotective natural cembranoid that reverses DFP-induced damage both in vivo and in the hippocampal slice. Cembranoid 1 acts by noncompetitive inhibition of the α7 nicotinic acetylcholine receptor. This study aims at establishing a preliminary structure-activity relationship to define the neuroprotective cembranoid pharmacophores using the hippocampal slice assay and pharmacophore modeling. Fourteen natural, semisyntheti or biocatalytic cembranoid analogues 2-15 related to 1 were tested for their capacity to protect the population spikes from DFP-induced damage and intrinsic toxicity. Twelve cembranoids caused significant reversal of DFP toxicity; only 3 active analogues displayed minor intrinsic toxicity at 10 μM. The C-4 epimer of 1 (2) and the 4-O-methyl ether analogue of 1 (3), were totally devoid of neuroprotective activity. The results suggested a model for cembranoid binding where the hydrophobic ring surface binds to a hydrophobic (Hbic) patch on the receptor molecule and an electronegative atom (oxygen or sulfur) in proper spatial relationship to the ring surface interacts with an electropositive group in the receptor binding site. A pharmacophore model consisting of 1 hydrogen bond acceptor (HBA), 2 Hbic, and 10 exclusion spheres was established using HipHop-REFINE and supported the above mentioned pharmacophoric hypothesis. PMID:23769165

  9. Protective activity of (1S,2E,4R,6R,7E,11E)-2,7,11-cembratriene-4,6-diol analogues against diisopropylfluorophosphate neurotoxicity: preliminary structure-activity relationship and pharmacophore modeling.

    PubMed

    Eterović, Vesna A; Del Valle-Rodriguez, Angelie; Pérez, Dinely; Carrasco, Marimée; Khanfar, Mohammad A; El Sayed, Khalid A; Ferchmin, Pedro A

    2013-08-01

    Diisopropylfluorophosphate (DFP) is an organophosphorous insecticide used as a surrogate for the more toxic chemical warfare nerve agent sarin. DFP produces neurotoxicity in vivo and irreversibly decreases the area of population spikes recorded from the CA1 region of acute hippocampal slices. (1S,2E,4R,6R,7E,11E)-2,7,11-Cembratriene-4,6-diol (1) is a neuroprotective natural cembranoid that reverses DFP-induced damage both in vivo and in the hippocampal slice. Cembranoid 1 acts by noncompetitive inhibition of the α7 nicotinic acetylcholine receptor. This study aims at establishing a preliminary structure-activity relationship to define the neuroprotective cembranoid pharmacophores using the hippocampal slice assay and pharmacophore modeling. Fourteen natural, semisynthetic, or biocatalytic cembranoid analogues 2-15 related to 1 were tested for their capacity to protect the population spikes from DFP-induced damage and intrinsic toxicity. Twelve cembranoids caused significant reversal of DFP toxicity; only 3 active analogues displayed minor intrinsic toxicity at 10 μM. The C-4 epimer of 1 (2) and the 4-O-methyl ether analogue of 1 (3), were totally devoid of neuroprotective activity. The results suggested a model for cembranoid binding where the hydrophobic ring surface binds to a hydrophobic (Hbic) patch on the receptor molecule and an electronegative atom (oxygen or sulfur) in proper spatial relationship to the ring surface interacts with an electropositive group in the receptor binding site. A pharmacophore model consisting of 1 hydrogen bond acceptor (HBA), 2 Hbic, and 10 exclusion spheres was established using HipHop-REFINE and supported the above mentioned pharmacophoric hypothesis. PMID:23769165

  10. Constructing and Validating 3D-pharmacophore Models to a Set of MMP-9 Inhibitors for Designing Novel Anti-melanoma Agents.

    PubMed

    Medeiros Turra, Kely; Pineda Rivelli, Diogo; Berlanga de Moraes Barros, Silvia; Mesquita Pasqualoto, Kerly Fernanda

    2016-07-01

    A receptor-independent (RI) four-dimensional structure-activity relationship (4D-QSAR) formalism was applied to a set of sixty-four β-N-biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP-9). MMP-9 belongs to a group of enzymes related to the cleavage of several extracellular matrix components and has been associated to cancer invasiveness/metastasis. The best RI 4D-QSAR model was statistically significant (N=47; r(2) =0.91; q(2) =0.83; LSE=0.09; LOF=0.35; outliers=0). Leave-N-out (LNO) and y-randomization approaches indicated the QSAR model was robust and presented no chance correlation, respectively. Furthermore, it also had good external predictability (82 %) regarding the test set (N=17). In addition, the grid cell occupancy descriptors (GCOD) of the predicted bioactive conformation for the most potent inhibitor were successfully interpreted when docked into the MMP-9 active site. The 3D-pharmacophore findings were used to predict novel ligands and exploit the MMP-9 calculated binding affinity through molecular docking procedure. PMID:27492238

  11. Snooker Structure-Based Pharmacophore Model Explains Differences in Agonist and Blocker Binding to Bitter Receptor hTAS2R39

    PubMed Central

    Roland, Wibke S. U.; Sanders, Marijn P. A.; van Buren, Leo; Gouka, Robin J.; Gruppen, Harry; Vincken, Jean-Paul; Ritschel, Tina

    2015-01-01

    The human bitter taste receptor hTAS2R39 can be activated by many dietary (iso)flavonoids. Furthermore, hTAS2R39 activity can be blocked by 6-methoxyflavanones, 4’-fluoro-6-methoxyflavanone in particular. A structure-based pharmacophore model of the hTAS2R39 binding pocket was built using Snooker software, which has been used successfully before for drug design of GPCRs of the rhodopsin subfamily. For the validation of the model, two sets of compounds, both of which contained actives and inactives, were used: (i) an (iso)flavonoid-dedicated set, and (ii) a more generic, structurally diverse set. Agonists were characterized by their linear binding geometry and the fact that they bound deeply in the hTAS2R39 pocket, mapping the hydrogen donor feature based on T5.45 and N3.36, analogues of which have been proposed to play a key role in activation of GPCRs. Blockers lack hydrogen-bond donors enabling contact to the receptor. Furthermore, they had a crooked geometry, which could sterically hinder movement of the TM domains upon receptor activation. Our results reveal characteristics of hTAS2R39 agonist and bitter blocker binding, which might facilitate the development of blockers suitable to counter the bitterness of dietary hTAS2R39 agonists in food applications. PMID:25729848

  12. Pharmacophore model prediction, 3D-QSAR and molecular docking studies on vinyl sulfones targeting Nrf2-mediated gene transcription intended for anti-Parkinson drug design.

    PubMed

    Athar, Mohd; Lone, Mohsin Yousuf; Khedkar, Vijay M; Jha, Prakash Chandra

    2016-06-01

    Despite intense research efforts towards clinical and molecular causes of Parkinson disease (PD), the etiology of disease still remains unclear. However, recent studies have provided ample evidences that the oxidative stress is the key player that contributes a lot to dopaminergic (DAergic) neurodegeneration in brain. It is due to the discrepancy of antioxidant defence system of which nuclear factor erythroid 2-related factor 2 (Nrf2) signalling is of central contour. In the current study, potent heme oxygenase-1 agonists (Nrf2 signalling regulator), vinyl sulfones, were selected and an optimal pharmacophore model was brought forth which was examined using a decoy set by atom-based 3D-QSAR. The best four-feature model consists of two hydrogen bond acceptors and two aromatic rings, which has the highest correlation coefficient, R(2) = .71 and [Formula: see text] = .73 in QSAR. These ligands were further studied for molecular docking with Nrf2-keap protein to gain insight into the major binding motifs followed by analysing pharmacokinetic properties to evaluate their bioavailability dominance. From this study, it is concluded that vinyl sulfones could be ideal compounds for targeting Nrf2 pathway which in turn halt the PD progression. Hence, these can be considered as potential leads for drug development against the same. PMID:26222438

  13. Snooker structure-based pharmacophore model explains differences in agonist and blocker binding to bitter receptor hTAS2R39.

    PubMed

    Roland, Wibke S U; Sanders, Marijn P A; van Buren, Leo; Gouka, Robin J; Gruppen, Harry; Vincken, Jean-Paul; Ritschel, Tina

    2015-01-01

    The human bitter taste receptor hTAS2R39 can be activated by many dietary (iso)flavonoids. Furthermore, hTAS2R39 activity can be blocked by 6-methoxyflavanones, 4'-fluoro-6-methoxyflavanone in particular. A structure-based pharmacophore model of the hTAS2R39 binding pocket was built using Snooker software, which has been used successfully before for drug design of GPCRs of the rhodopsin subfamily. For the validation of the model, two sets of compounds, both of which contained actives and inactives, were used: (i) an (iso)flavonoid-dedicated set, and (ii) a more generic, structurally diverse set. Agonists were characterized by their linear binding geometry and the fact that they bound deeply in the hTAS2R39 pocket, mapping the hydrogen donor feature based on T5.45 and N3.36, analogues of which have been proposed to play a key role in activation of GPCRs. Blockers lack hydrogen-bond donors enabling contact to the receptor. Furthermore, they had a crooked geometry, which could sterically hinder movement of the TM domains upon receptor activation. Our results reveal characteristics of hTAS2R39 agonist and bitter blocker binding, which might facilitate the development of blockers suitable to counter the bitterness of dietary hTAS2R39 agonists in food applications. PMID:25729848

  14. Modification of PBDEs (BDE-15, BDE-47, BDE-85 and BDE-126) biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential based on the pharmacophore modeling assistant with the full factor experimental design.

    PubMed

    Jiang, Long; Li, Yu

    2016-04-15

    In this study, the properties of AhR binding affinity, bio-concentration factor, half-life and vapor pressure were selected as the typical indicators of biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential for polybrominated diphenyl ethers (PBDEs), respectively. A three-dimensional pharmacophore modeling assistant with a full factor experimental design for each property was used to reveal the significant pharmacophore features and the substituent effects to obtain reasonable modified schemes for the selected target PBDEs. Finally, the performances of the persistent organic pollutant (POP) properties, the synthesis feasibility and the fire resistance of the modified compounds were evaluated. The most influential pharmacophore feature for all POP properties was the hydrophobic group, especially the vinyl and propyl groups. Modified compounds with two additional hydrophobic groups exhibited a better regulatory performance. The average reduction in the proportions of the four POP properties for the modified compounds (except for 3-phenyl-BDE-15) was 70.60%, 52.44%, 47.04% and 70.88%. In addition, the energy and the C-Br bond dissociation enthalpy of the four typical PBDEs were higher than those of the modified compounds (except for 3-phenyl-BDE-15), indicating the synthesis feasibility and the lower energy barrier of the modified compounds to release Br free radicals to provide fire resistance. PMID:26785211

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

    PubMed

    Chaudhari, Prashant; Bari, Sanjay

    2016-02-01

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

  16. Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

    PubMed

    Lee, Sehan; Barron, Mace G

    2015-11-01

    Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based approaches have been successfully applied to AChE inhibitors (AChEIs). The major limitation of these approaches has been the small applicability domain due to the lack of structural diversity in the training set. In this study, we developed a 3 dimensional quantitative structure-activity relationship (3D-QSAR) for inhibitory activity of 89 reversible and irreversible AChEIs including drugs and insecticides. A 3D-fingerprint descriptor encoding protein-ligand interactions was developed using molecular docking and structure-based pharmacophore to rationalize the structural requirements responsible for the activity of these compounds. The obtained 3D-QSAR model exhibited high correlation value (R(2) = 0.93) and low mean absolute error (MAE = 0.32 log units) for the training set (n = 63). The model was predictive across a range of structures as shown by the leave-one-out cross-validated correlation coefficient (Q(2) = 0.89) and external validation results (n = 26, R(2) = 0.89, and MAE = 0.38 log units). The model revealed that the compounds with high inhibition potency had proper conformation in the active site gorge and interacted with key amino acid residues, in particular Trp84 and Phe330 at the catalytic anionic site, Trp279 at the peripheral anionic site, and Gly118, Gly119, and Ala201 at the oxyanion hole. The resulting universal 3D-QSAR model provides insight into the multiple molecular interactions determining AChEI potency that may guide future chemical design and regulation of toxic AChEIs. PMID:26202430

  17. A Substrate Pharmacophore for the Human Organic Cation/Carnitine Transporter Identifies Compounds Associated with Rhabdomyolysis

    PubMed Central

    Ekins, Sean; Diao, Lei; Polli, James E.

    2012-01-01

    The human Organic Cation/Carnitine Transporter (hOCTN2), is a high affinity cation/carnitine transporter expressed widely in human tissues and is physiologically important for the homeostasis of L-carnitine. The objective of this study was to elucidate the substrate requirements of this transporter via computational modelling based on published in vitro data. Nine published substrates of hOCTN2 were used to create a common features pharmacophore that was validated by mapping other known OCTN2 substrates. The pharmacophore was used to search a drug database and retrieved molecules that were then used as search queries in PubMed for instances of a side effect (rhabdomyolysis) associated with interference with L-carnitine transport. The substrate pharmacophore was comprised of two hydrogen bond acceptors, a positive ionizable feature and ten excluded volumes. The substrate pharmacophore also mapped 6 out of 7 known substrate molecules used as a test set. After searching a database of ~800 known drugs, thirty drugs were predicted to map to the substrate pharmacophore with L-carnitine shape restriction. At least 16 of these molecules had case reports documenting an association with rhabdomyolysis and represent a set for prioritizing for future testing as OCTN2 substrates or inhibitors. This computational OCTN2 substrate pharmacophore derived from published data partially overlaps a previous OCTN2 inhibitor pharmacophore and is also able to select compounds that demonstrate rhabdomyolysis, further confirming the possible linkage between this side effect and hOCTN2. PMID:22339151

  18. Toll-like receptor 7 agonists: chemical feature based pharmacophore identification and molecular docking studies.

    PubMed

    Yu, Hui; Jin, Hongwei; Sun, Lidan; Zhang, Liangren; Sun, Gang; Wang, Zhanli; Yu, Yongchun

    2013-01-01

    Chemical feature based pharmacophore models were generated for Toll-like receptors 7 (TLR7) agonists using HypoGen algorithm, which is implemented in the Discovery Studio software. Several methods tools used in validation of pharmacophore model were presented. The first hypothesis Hypo1 was considered to be the best pharmacophore model, which consists of four features: one hydrogen bond acceptor, one hydrogen bond donor, and two hydrophobic features. In addition, homology modeling and molecular docking studies were employed to probe the intermolecular interactions between TLR7 and its agonists. The results further confirmed the reliability of the pharmacophore model. The obtained pharmacophore model (Hypo1) was then employed as a query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit was identified as a potent TLR7 agonist, which has antiviral activity against hepatitis virus in vitro. Therefore, our current work provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 agonists with desired biological activity. PMID:23526932

  19. Discovery of novel mGluR1 antagonists: a multistep virtual screening approach based on an SVM model and a pharmacophore hypothesis significantly increases the hit rate and enrichment factor.

    PubMed

    Li, Guo-Bo; Yang, Ling-Ling; Feng, Shan; Zhou, Jian-Ping; Huang, Qi; Xie, Huan-Zhang; Li, Lin-Li; Yang, Sheng-Yong

    2011-03-15

    Development of glutamate non-competitive antagonists of mGluR1 (Metabotropic glutamate receptor subtype 1) has increasingly attracted much attention in recent years due to their potential therapeutic application for various nervous disorders. Since there is no crystal structure reported for mGluR1, ligand-based virtual screening (VS) methods, typically pharmacophore-based VS (PB-VS), are often used for the discovery of mGluR1 antagonists. Nevertheless, PB-VS usually suffers a lower hit rate and enrichment factor. In this investigation, we established a multistep ligand-based VS approach that is based on a support vector machine (SVM) classification model and a pharmacophore model. Performance evaluation of these methods in virtual screening against a large independent test set, M-MDDR, show that the multistep VS approach significantly increases the hit rate and enrichment factor compared with the individual SB-VS and PB-VS methods. The multistep VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally a total of 20 compounds were selected from the top ranking compounds, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future. PMID:21316965

  20. Validation of formylchromane derivatives as protein tyrosine phosphatase 1B inhibitors by pharmacophore modeling, atom-based 3D-QSAR and docking studies.

    PubMed

    Malla, Priyanka; Kumar, Rajnish; Kumar, Manoj

    2013-07-01

    Formylchromane derivatives were reported to possess irreversible and selective inhibition on human protein tyrosine phosphatase 1B (PTP 1B). Inhibition of PTP 1B is a molecular level legitimate approach for the management of type 2 diabetes mellitus (T2DM). 3D-QSAR studies were performed on a series of formylchromane derivatives using partial least square (PLS) analysis for correlating molecular architecture of the analogs with their PTP 1B inhibitory activity. A five-point pharmacophore hypothesis with three hydrogen bond acceptors (A) and two aromatic rings (R) as pharmacophoric features was developed using phase module of Schrödinger suite. The hypothesis AAARR.160 was considered as best hypothesis in this study characterized by survival score (3.483), the best cross-validated r² (Q²) (0.774), regression coefficient (0.960), Pearson-R (0.891), and F value (100.3). The results of hypothesis AAARR.160 complimented very closely to interactions witnessed in active site of the ligand-bound complex. The molecular docking simulations into PTP 1B active site also highlighted that biphenyl moiety favorably interacted with amino acid residues lining the lipophilic pocket, and provided hydrophobic interactions with receptor active site. These observations might be useful for further development and optimization of new chemical entities as potential PTP 1B inhibitors prior to its synthesis. PMID:23506477

  1. Characterization of interactions and pharmacophore development for DFG-out inhibitors to RET tyrosine kinase.

    PubMed

    Gao, Chunxia; Grøtli, Morten; Eriksson, Leif A

    2015-07-01

    RET (rearranged during transfection) tyrosine kinase is a promising target for several human cancers. Abt-348, Birb-796, Motesanib and Sorafenib are DFG-out multi-kinase inhibitors that have been reported to inhibit RET activity with good IC50 values. Although the DFG-out conformation has attracted great interest in the design of type II inhibitors, the structural requirements for binding to the RET DFG-out conformation remains unclear. Herein, the DFG-out conformation of RET was determined by homology modelling, the four inhibitors were docked, and the binding modes investigated by molecular dynamics simulation. Binding free energies were calculated using the molecular mechanics/Poisson-Bolzmann surface area (MM/PBSA) method. The trends in predicted binding free affinities correlated well with experimental data and were used to explain the activity difference of the studied inhibitors. Per-residue energy decomposition analyses provided further information on specific interaction properties. Finally, we also conducted a detailed e-pharmacophore modelling of the different RET-inhibitor complexes, explaining the common and specific pharmacophore features of the different complexes. The results reported herein will be useful in future rational design of novel DFG-out RET inhibitors. PMID:26044359

  2. A Novel Approach for Efficient Pharmacophore-based Virtual Screening: Method and Applications

    PubMed Central

    Dror, Oranit; Schneidman-Duhovny, Dina; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.

    2009-01-01

    Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to: (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used dataset of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) dataset was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening. Availability The software is available for download. A user-friendly web interface for pharmacophore detection is available at http://bioinfo3d.cs.tau.ac.il/PharmaGist. PMID:19803502

  3. ZINCPharmer: pharmacophore search of the ZINC database

    PubMed Central

    Koes, David Ryan; Camacho, Carlos J.

    2012-01-01

    ZINCPharmer (http://zincpharmer.csb.pitt.edu) is an online interface for searching the purchasable compounds of the ZINC database using the Pharmer pharmacophore search technology. A pharmacophore describes the spatial arrangement of the essential features of an interaction. Compounds that match a well-defined pharmacophore serve as potential lead compounds for drug discovery. ZINCPharmer provides tools for constructing and refining pharmacophore hypotheses directly from molecular structure. A search of 176 million conformers of 18.3 million compounds typically takes less than a minute. The results can be immediately viewed, or the aligned structures may be downloaded for off-line analysis. ZINCPharmer enables the rapid and interactive search of purchasable chemical space. PMID:22553363

  4. Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores.

    PubMed

    Lagarde, Nathalie; Delahaye, Solenne; Zagury, Jean-François; Montes, Matthieu

    2016-01-01

    Nuclear receptors (NRs) constitute an important class of therapeutic targets. We evaluated the performance of 3D structure-based and ligand-based pharmacophore models in predicting the pharmacological profile of NRs ligands using the NRLiSt BDB database. We could generate selective pharmacophores for agonist and antagonist ligands and we found that the best performances were obtained by combining the structure-based and the ligand-based approaches. The combination of pharmacophores that were generated allowed to cover most of the chemical space of the NRLiSt BDB datasets. By screening the whole NRLiSt BDB on our 3D pharmacophores, we demonstrated their selectivity towards their dedicated NRs ligands. The 3D pharmacophores herein presented can thus be used as a predictor of the pharmacological activity of NRs ligands.Graphical AbstractUsing a combination of structure-based and ligand-based pharmacophores, agonist and antagonist ligands of the Nuclear Receptors included in the NRLiSt BDB database could be separated. PMID:27602059

  5. Development of pharmacophore similarity-based quantitative activity hypothesis and its applicability domain: applied on a diverse data-set of HIV-1 integrase inhibitors.

    PubMed

    Kumar, Sivakumar Prasanth; Jasrai, Yogesh T; Mehta, Vijay P; Pandya, Himanshu A

    2015-01-01

    Quantitative pharmacophore hypothesis combines the 3D spatial arrangement of pharmacophore features with biological activities of the ligand data-set and predicts the activities of geometrically and/or pharmacophoric similar ligands. Most pharmacophore discovery programs face difficulties in conformational flexibility, molecular alignment, pharmacophore features sampling, and feature selection to score models if the data-set constitutes diverse ligands. Towards this focus, we describe a ligand-based computational procedure to introduce flexibility in aligning the small molecules and generating a pharmacophore hypothesis without geometrical constraints to define pharmacophore space, enriched with chemical features necessary to elucidate common pharmacophore hypotheses (CPHs). Maximal common substructure (MCS)-based alignment method was adopted to guide the alignment of carbon molecules, deciphered the MCS atom connectivity to cluster molecules in bins and subsequently, calculated the pharmacophore similarity matrix with the bin-specific reference molecules. After alignment, the carbon molecules were enriched with original atoms in their respective positions and conventional pharmacophore features were perceived. Distance-based pharmacophoric descriptors were enumerated by computing the interdistance between perceived features and MCS-aligned 'centroid' position. The descriptor set and biological activities were used to develop support vector machine models to predict the activities of the external test set. Finally, fitness score was estimated based on pharmacophore similarity with its bin-specific reference molecules to recognize the best and poor alignments and, also with each reference molecule to predict outliers of the quantitative hypothesis model. We applied this procedure to a diverse data-set of 40 HIV-1 integrase inhibitors and discussed its effectiveness with the reported CPH model. PMID:24735019

  6. In vitro and pharmacophore insights into CYP3A enzymes.

    PubMed

    Ekins, Sean; Stresser, David M; Williams, J Andrew

    2003-04-01

    The cytochrome P450 3A (CYP3A) enzymes have a major role in the metabolism of drugs in humans. Their wide substrate specificity and induction by a vast array of structurally diverse compounds presents the possibility of metabolic drug-drug interactions. Understanding the enzymes themselves is crucial. Over the past decade, this has occurred mostly with in vitro studies, although more recent approaches incorporate computational models to predict CYP inhibition and substrate potential. The three-dimensional displacement, or pharmacophore, of chemical features in space that are derived from inhibition data have produced pharmacophores for CYP3A4, CYP3A5 and CYP3A7, and provide new insights into ligand binding for each enzyme. PMID:12707001

  7. Pharmacophore mapping based inhibitor selection and molecular interaction studies for identification of potential drugs on calcium activated potassium channel blockers, tamulotoxin

    PubMed Central

    Kumar, R. Barani; Suresh, M. Xavier

    2013-01-01

    Background: Tamulotoxin (TmTx) from Buthus tamulus was found to be a highly venomous toxin which accelerates the neurotransmitter release that directly affects the cardiovascular tissues and the respiratory system leading to death. TmTx from red Indian scorpion is a crucial inhibitor for Ca2+ activated K+ channel in humans. Objective: The study is aimed at the identification of potential inhibitors of TmTx through pharmacophore based inhibitor screening and understanding the molecular level interactions. Materials and Method: The potential inhibitors for TmTx were identified using pharmacophore model based descriptor information present in existing drugs with the analysis of pharmacokinetic properties. The compounds with good ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) descriptors were subjected to molecular interaction studies. The stability of bound toxin-inhibitor complex was studied using molecular dynamics simulation over a period of one nanosecond. Results: From a dataset of 3406 compounds, few compounds were selected as potential inhibitors based on the generated best pharmacophore models, pharmacokinetic analysis, molecular docking and molecular dynamics studies. Conclusion: In conclusion, two compounds containing better inhibition properties against TmTx are suggested to be better lead molecules for drug development in future and this study will help us to explore more inhibitors from natural origin against tamulotoxin. PMID:23772102

  8. Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification.

    PubMed

    Krovat, Eva M; Langer, Thierry

    2003-02-27

    Chemical feature based pharmacophore models were elaborated for angiotensin II receptor subtype 1 (AT(1)) antagonists using both a quantitative and a qualitative approach (Catalyst HypoGen and HipHop algorithms, respectively). The training sets for quantitative model generation consisted of 25 selective AT(1) antagonists exhibiting IC(50) values ranging from 1.3 nM to 150 microM. Additionally, a qualitative pharmacophore hypothesis was derived from multiconformational structure models of the two highly active AT(1) antagonists 4u (IC(50) = 0.2 nM) and 3k (IC(50) = 0.7 nM). In the case of the quantitative model, the best pharmacophore hypothesis consisted of a five-features model (Hypo1: seven points, one hydrophobic aromatic, one hydrophobic aliphatic, a hydrogen bond acceptor, a negative ionizable function, and an aromatic plane function). The best qualitative model consisted of seven features (Hypo2: 11 points, two aromatic rings, two hydrogen bond acceptors, a negative ionizable function, and two hydrophobic functions). The obtained pharmacophore models were validated on a wide set of test molecules. They were shown to be able to identify a range of highly potent AT(1) antagonists, among those a number of recently launched drugs and some candidates presently undergoing clinical tests and/or development phases. The results of our study provide confidence for the utility of the selected chemical feature based pharmacophore models to retrieve structurally diverse compounds with desired biological activity by virtual screening. PMID:12593652

  9. Elucidation of the Teixobactin Pharmacophore.

    PubMed

    Yang, Hyunjun; Chen, Kevin H; Nowick, James S

    2016-07-15

    This paper elucidates the teixobactin pharmacophore by comparing the arginine analogue of teixobactin Arg10-teixobactin to seven homologues with varying structure and stereochemistry. The roles of the guanidinium group at position 10, the stereochemistry of the macrolactone ring, and the "tail" comprising residues 1-5 are investigated. The guanidinium group is not necessary for activity; Lys10-teixobactin is more active than Arg10-teixobactin against Gram-positive bacteria in minimum inhibitory concentration (MIC) assays. The relative stereochemistry of the macrolactone ring is important. Diastereomer l-Thr8,Arg10-teixobactin is inactive, and diastereomer d-allo-Ile11,Arg10-teixobactin is less active. The macrolactone ring is critical; seco-Arg10-teixobactin is inactive. The absolute stereochemistry is not important; the enantiomer ent-Arg10-teixobactin is comparable in activity. The hydrophobic N-terminal tail is important. Truncation of residues 1-5 results in loss of activity, and replacement of residues 1-5 with a dodecanoyl group partially restores activity. These findings pave the way for developing simpler homologues of teixobactin with enhanced pharmacological properties. PMID:27232661

  10. Substructural QSAR approaches and topological pharmacophores.

    PubMed Central

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

    1985-01-01

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

  11. Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs.

    PubMed

    Wang, Xia; Pan, Chenxu; Gong, Jiayu; Liu, Xiaofeng; Li, Honglin

    2016-06-27

    PharmMapper is a web server for drug target identification by reversed pharmacophore matching the query compound against an annotated pharmacophore model database, which provides a computational polypharmacology prediction approach for drug repurposing and side effect risk evaluation. But due to the inherent nondiscriminative feature of the simple fit scores used for prediction results ranking, the signal/noise ratio of the prediction results is high, posing a challenge for predictive reliability. In this paper, we improved the predictive accuracy of PharmMapper by generating a ligand-target pairwise fit score matrix from profiling all the annotated pharmacophore models against corresponding ligands in the original complex structures that were used to extract these pharmacophore models. The matrix reflects the noise baseline of fit score distribution of the background database, thus enabling estimation of the probability of finding a given target randomly with the calculated ligand-pharmacophore fit score. Two retrospective tests were performed which confirmed that the probability-based ranking score outperformed the simple fit score in terms of identification of both known drug targets and adverse drug reaction related off-targets. PMID:27187084

  12. Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking.

    PubMed

    Ren, Ji-Xia; Li, Lin-Li; Zheng, Ren-Lin; Xie, Huan-Zhang; Cao, Zhi-Xing; Feng, Shan; Pan, You-Li; Chen, Xin; Wei, Yu-Quan; Yang, Sheng-Yong

    2011-06-27

    In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors. PMID:21618971

  13. Towards a Pharmacophore for Amyloid

    SciTech Connect

    Landau, Meytal; Sawaya, Michael R.; Faull, Kym F.; Laganowsky, Arthur; Jiang, Lin; Sievers, Stuart A.; Liu, Jie; Barrio, Jorge R.; Eisenberg, David

    2011-09-16

    may be required for future amyloid therapies. The structures described here start to define the amyloid pharmacophore, opening the way to structure-based design of improved diagnostics and therapeutics.

  14. [Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

    PubMed

    He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

    2014-11-01

    By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive. PMID:25850277

  15. Flexible and biomimetic analogs of triple uptake inhibitor 4-((((3S,6S)-6-benzhydryltetrahydro-2H-pyran-3-yl)amino)methyl)phenol : Synthesis, biological characterization, and development of a pharmacophore model

    PubMed Central

    Sharma, Horrick; Santra, Soumava; Debnath, Joy; Antonio, Tamara; Reith, Maarten; Dutta, Aloke

    2014-01-01

    In this study we have generated a pharmacophore model of triple uptake inhibitor compounds based on novel asymmetric pyran derivatives and the newly developed asymmetric furan derivatives. The model revealed features important for inhibitors to exhibit a balanced activity against dopamine transporter (DAT), serotonin transporter (SERT), and norepinephrine transporter (NET). In particular, a ‘folded’ conformation was found common to the active pyran compounds in the training set and was crucial to triple uptake inhibitory activity. Furthermore, the distances between the benzhydryl moiety and the N-benzyl group as well as the orientation of the secondary nitrogen were also important for TUI activity. We have validated our findings by synthesizing and testing novel asymmetric pyran analogs. The present work has also resulted in the discovery of a new series of asymmetric tetrahydrofuran derivatives as novel TUIs. Lead compounds 41 and 42 exhibited moderate TUI activity. Interestingly, the highest TUI activity by lead tetrahydrofuran compounds e.g. 41 and 42, was exhibited in a stereochemical preference similar to pyran TUI e.g. D-161. PMID:24315194

  16. ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

    PubMed

    Wang, Shuangquan; Sun, Huiyong; Liu, Hui; Li, Dan; Li, Youyong; Hou, Tingjun

    2016-08-01

    Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. In this study, pharmacophore modeling and machine learning approaches were combined to construct classification models to distinguish hERG active from inactive compounds based on a diverse data set. First, an optimal ensemble of pharmacophore hypotheses that had good capability to differentiate hERG active from inactive compounds was identified by the recursive partitioning (RP) approach. Then, the naive Bayesian classification (NBC) and support vector machine (SVM) approaches were employed to construct classification models by integrating multiple important pharmacophore hypotheses. The integrated classification models showed improved predictive capability over any single pharmacophore hypothesis, suggesting that the broad binding polyspecificity of hERG can only be well characterized by multiple pharmacophores. The best SVM model achieved the prediction accuracies of 84.7% for the training set and 82.1% for the external test set. Notably, the accuracies for the hERG blockers and nonblockers in the test set reached 83.6% and 78.2%, respectively. Analysis of significant pharmacophores helps to understand the multimechanisms of action of hERG blockers. We believe that the combination of pharmacophore modeling and SVM is a powerful strategy to develop reliable theoretical models for the prediction of potential hERG liability. PMID:27379394

  17. GRID-based three-dimensional pharmacophores I: FLAPpharm, a novel approach for pharmacophore elucidation.

    PubMed

    Cross, Simon; Baroni, Massimo; Goracci, Laura; Cruciani, Gabriele

    2012-10-22

    Pharmacophore elucidation approaches are routinely used in drug discovery, primarily with the aim of determining the three-dimensional arrangement of common features shared by ligands interacting at the site of interest; these features can then be used to investigate the structure-activity relationship between the ligands and also to screen for other molecules possessing the relevant features. Here we present a novel approach based on GRID molecular interaction fields and the derivative method FLAP that has been previously described, which provides a common reference framework to compare both small molecule ligands and macromolecular protein targets. Unlike classical pharmacophore elucidation approaches that extract simplistic molecular features, determine those which are common across the data set, and use these features to align the structures, FLAPpharm first aligns the structures and subsequently extracts the common interacting features in terms of their molecular interaction fields, pseudofields, and atomic points, representing the common pharmacophore as a more comprehensive pharmacophoric pseudomolecule. The approach is applied to a number of data sets to investigate performance in terms of reproducing the X-ray crystallography-based alignment, in terms of its discriminatory ability when applied to virtual screening and also to illustrate its ability to explain alternative binding modes. In part two of this publication, a comprehensive benchmark data set for pharmacophore elucidation is presented and the performance of FLAPpharm discussed. PMID:22970894

  18. GALAHAD: 1. pharmacophore identification by hypermolecular alignment of ligands in 3D.

    PubMed

    Richmond, Nicola J; Abrams, Charlene A; Wolohan, Philippa R N; Abrahamian, Edmond; Willett, Peter; Clark, Robert D

    2006-09-01

    Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target. PMID:17051338

  19. A common pharmacophoric footprint for AIDS vaccine design.

    PubMed

    Pisterer, Christoph; Mihailescu, Dan; Smith, Jeremy C; Reed, Jennifer

    2004-07-15

    The most promising target antigen for an HIV vaccine designed using the classic antibody strategy has been the viral coat protein gp120. Unfortunately, its high variability has prevented this approach. We examine here a 15-residue peptide derived from the CD4-binding domain of gp120. By use of molecular dynamics computer simulation, it is shown that despite considerable sequence variation, the three-dimensional structure of the peptide is preserved over the full range of clade-specific sequences. Furthermore, sequences threaded onto the structure exhibit common three-dimensional electrostatic and hydrophobic properties. These common physicochemical characteristics constitute a pharmacophoric footprint that promises to be useful in the design of a synthetic antigen for vaccine development. PMID:15239651

  20. E-pharmacophore-based virtual screening to identify GSK-3β inhibitors.

    PubMed

    Natarajan, Pradeep; Priyadarshini, Vani; Pradhan, Dibyabhaba; Manne, Munikumar; Swargam, Sandeep; Kanipakam, Hema; Bhuma, Vengamma; Amineni, Umamaheswari

    2016-10-01

    Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer's disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50 ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β. PMID:27305963

  1. Modeling Climate Dynamically

    ERIC Educational Resources Information Center

    Walsh, Jim; McGehee, Richard

    2013-01-01

    A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

  2. [Study on lipid-lowering traditional Chinese medicines based on pharmacophore technology and patent retrieval].

    PubMed

    Huo, Xiao-qian; He, Yu-su; Qiao, Lian-sheng; Sun, Zhi-yi; Zhang, Yan-ling

    2014-12-01

    The combined application of statins that inhibit HMG-CoA reductase and fibrates that activate PPAR-α can produce a better lipid-lowering effect than the simple application, but with stronger adverse reactions at the same time. In the treatment of hyperlipidemia, the combined administration of TCMs and HMG-CoA reductase inhibitor in treating hyperlipidemia shows stable efficacy and less adverse reactions, and provides a new option for the combined application of drugs. In this article, the pharmacophore technology was used to search chemical components of TCMs, trace their source herbs, and determine the potential common TCMs that could activate PPAR-α. Because there is no hyperlipidemia-related medication reference in modern TCM classics, to ensure the high safety and efficacy of all selected TCMs, we selected TCMs that are proved to be combined with statins in the World Traditional/Natural Medicine Patent Database, analyzed corresponding drugs in pharmacophore results based on that, and finally obtained common TCMs that can be applied in PPAR-α and combined with statins. Specifically, the pharmacophore model was based on eight receptor-ligand complexes of PPAR-α. The Receptor-Ligand Pharmacophore Generation module in the DS program was used to build the model, optimize with the Screen Library module, and get the best sub-pharmacophore, which consisted of two hydrogen bond acceptor, three hydrophobic groups and 19 excluded volumes, with the identification effectiveness index value N of 2. 82 and the comprehensive evaluation index CAI value of 1. 84. The model was used to screen the TCMD database, hit 5,235 kinds of chemical components and 1 193 natural animals and plants, and finally determine 62 TCMs. Through patent retrieval, we found 38 TCMs; After comparing with the virtual screening results, we finally got seven TCMs. PMID:25898588

  3. PharmaGist: a webserver for ligand-based pharmacophore detection

    PubMed Central

    Schneidman-Duhovny, Dina; Dror, Oranit; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.

    2008-01-01

    Predicting molecular interactions is a major goal in rational drug design. Pharmacophore, which is the spatial arrangement of features that is essential for a molecule to interact with a specific target receptor, is an important model for achieving this goal. We present a freely available web server, named PharmaGist, for pharmacophore detection. The employed method is ligand based. Namely, it does not require the structure of the target receptor. Instead, the input is a set of structures of drug-like molecules that are known to bind to the receptor. The output consists of candidate pharmacophores that are computed by multiple flexible alignment of the input ligands. The method handles the flexibility of the input ligands explicitly and in deterministic manner within the alignment process. PharmaGist is also highly efficient, where a typical run with up to 32 drug-like molecules takes seconds to a few minutes on a stardard PC. Another important characteristic is the capability of detecting pharmacophores shared by different subsets of input molecules. This capability is a key advantage when the ligands belong to different binding modes or when the input contains outliers. The webserver has a user-friendly interface available at http://bioinfo3d.cs.tau.ac.il/PharmaGist. PMID:18424800

  4. New features that improve the pharmacophore tools from Accelrys.

    PubMed

    Sutter, Jon; Li, Jiabo; Maynard, Allister J; Goupil, Anne; Luu, Tien; Nadassy, Katalin

    2011-09-01

    Generating a pharmacophore is often the first step towards understanding the interactions between a receptor and a ligand and can be pivotal to a successful drug discovery project. The pharmacophore tools at Accelrys have been used to assist in many different projects over the years, such as lead generation, scaffold hopping, mining ligand databases as well as many more. In this article, we will review the pharmacophore tools that have been developed at Accelrys. These will include the often used and well validated ligand based algorithms, HipHop and HypoGen and as well as extensions of these algorithms, HipHopRefine and HypoGenRefine. Recently we also developed new pharmacophore tools in the area of structure based design - deriving pharmacophores from the receptor as well as the receptor-ligand complex - which will also be discussed in this paper. PMID:21726193

  5. Setting the record straight: the origin of the pharmacophore concept.

    PubMed

    Güner, Osman F; Bowen, J Phillip

    2014-05-27

    For over a century since the early 1900s, Paul Ehrlich was credited with originating the concept of pharmacophores. This was challenged by John Van Drie in 2007 due to the fact that Ehrlich did not use the word "pharmacophore" in his writings. Van Drie claimed that the attribution of the pharmacophore concept to Ehrlich was due to an erroneous citation made by Ariëns in a 1966 paper, and instead he claimed, Lemont B. Kier developed the pharmacophore concept (in the modern sense, as defined by the IUPAC) during 1967-1971. There are two separate issues that may have triggered this conflict. The first one is the shift in the meaning of pharmacophore from "chemical groups" to patterns of "abstract features" of a molecule that are responsible for a biological effect. Indeed, the original use of the term is different than the current definition proposed by the IUPAC. The term was redefined in 1960 by Schueler, and this modification formed the basis of IUPAC's modern definition. The second issue is the origin of the "concept" of pharmacophore. While Ehrlich's contemporaries have consistently attributed the origin of the concept to him, the issue is further complicated by the fact that Ehrlich did not use the term pharmacophore in his papers. He, instead, referred to the features of a molecule that are responsible for biological effects as toxophores, while his contemporaries were using the term pharmacophore for the same features. In this paper, we resolve any doubts about the origins of the pharmacophore concept. Our research points to Paul Ehrlich's 1898 paper for originating the concept, which identifies peripheral chemical groups in molecules responsible for binding that leads to the subsequent biological effect, and to Schueler's 1960 book that extends the concept to the modern definition where spatial patterns of abstract features of a molecule define the pharmacophore and are ultimately responsible for the biological effect. PMID:24745881

  6. Angiotensin-I-converting enzyme inhibitory peptides: Chemical feature based pharmacophore generation.

    PubMed

    Wang, Zhanli; Zhang, Saisai; Jin, Hongwei; Wang, Wei; Huo, Jianxin; Zhou, Lishe; Wang, Yongfu; Feng, Fengqin; Zhang, Liangren

    2011-08-01

    A validated 3D pharmacophore model was generated for a series of ACE inhibitory peptides, which consisted of five features (two hydrophobic functions, two hydrogen bond acceptors, and a negative ionizable function). The built model was able to correctly predict the activity of known ACE inhibitors. The model was then used as query to search 3D databases of peptides. Three novel peptides (I, II and III) were synthesized and biologically evaluated in vitro. It appears that the in vitro activity of peptides I, II and III was consistent with their molecular modeling results. Our results provided confidence for the utility of the pharmacophore model to retrieve novel ACE inhibitory peptides with desired biological activity by virtual screening. PMID:21621881

  7. Multivariate PLS Modeling of Apicomplexan FabD-Ligand Interaction Space for Mapping Target-Specific Chemical Space and Pharmacophore Fingerprints

    PubMed Central

    Surolia, Avadhesha

    2015-01-01

    Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads. PMID:26535573

  8. Analysis of the binding mode of laulimalide to microtubules: Establishing a laulimalide-tubulin pharmacophore.

    PubMed

    Churchill, Cassandra D M; Klobukowski, Mariusz; Tuszynski, Jack A

    2016-07-01

    Laulimalide (LA) is a microtubule-stabilizing agent, currently in preclinical studies. However, studying the binding of this species and successfully synthesizing potent analogues have been challenging. The LA binding site is located between tubulin protofilaments, and therefore LA is in contact with two adjacent [Formula: see text]-tubulin units. Here, an improved model of the binding mode of LA in microtubules is presented, using the newly available crystal structure pose and an extended tubulin heterodimer complex, as well as molecular dynamics simulations. With this model, a series of LA analogues developed by Mooberry and coworkers are also analyzed in order to establish important pharmacophores in LA binding and cytotoxicity. In the side chain, [Formula: see text]-[Formula: see text] interactions are important contributors to LA binding, as are water-mediated hydrogen bonds. An intramolecular hydrogen bond is correlated with high cytotoxicity, and is dependent on macrocycle conformation. Therefore, while the epoxide and olefin groups in the macrocycle do not engage in specific interactions with the protein, they are essential contributions to an active macrocycle conformation, and therefore potency. Calculations reveal that a balance in binding affinity is important for LA activity, where the more potent compounds have larger interactions with the adjacent tubulin unit than the less-active analogs. Several modifications are suggested for the rational design of LA analogues that should not disrupt the active macrocycle conformation. PMID:26230757

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

    PubMed

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

    2007-03-01

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

  10. Dynamical model for thyroid

    NASA Astrophysics Data System (ADS)

    Rokni Lamooki, Gholam Reza; Shirazi, Amir H.; Mani, Ali R.

    2015-05-01

    Thyroid's main chemical reactions are employed to develop a mathematical model. The presented model is based on differential equations where their dynamics reflects many aspects of thyroid's behavior. Our main focus here is the well known, but not well understood, phenomenon so called as Wolff-Chaikoff effect. It is shown that the inhibitory effect of intake iodide on the rate of one single enzyme causes a similar effect as Wolff-Chaikoff. Besides this issue, the presented model is capable of revealing other complex phenomena of thyroid hormones homeostasis.

  11. Dynamic Triggering Stress Modeling

    NASA Astrophysics Data System (ADS)

    Gonzalez-Huizar, H.; Velasco, A. A.

    2008-12-01

    It has been well established that static (permanent) stress changes can trigger nearby earthquakes, within a few fault lengths from the causative event, whereas triggering by dynamic (transient) stresses carried by seismic waves both nearby and at remote distances has not been as well documented nor understood. An analysis of the change in the local stress caused by the passing of surfaces waves is important for the understanding of this phenomenon. In this study, we modeled the change in the stress that the passing of Rayleigh and Loves waves causes on a fault plane of arbitrary orientation, and applied a Coulomb failure criteria to calculate the potential of these stress changes to trigger reverse, normal or strike-slip failure. We preliminarily test these model results with data from dynamically triggering earthquakes in the Australian Bowen Basin. In the Bowen region, the modeling predicts a maximum triggering potential for Rayleigh waves arriving perpendicularly to the strike of the reverse faults present in the region. The modeled potentials agree with our observations, and give us an understanding of the dynamic stress orientation needed to trigger different type of earthquakes.

  12. De novo design of caseinolytic protein proteases inhibitors based on pharmacophore and 2D molecular fingerprints.

    PubMed

    Wu, Guanzhong; Zhang, Zhen; Chen, Hong; Lin, Kejiang

    2015-06-01

    Caseinolytic protein proteases (ClpP) are large oligomeric protein complexes that contribute to cell homeostasis as well as virulence regulation in bacteria. Inhibitors of ClpP can significantly attenuate the capability to produce virulence factors of the bacteria. In this work, we developed a workflow to expand the chemical space of potential ClpP inhibitors based on a set of β-lactones. In our workflow, an artificial pharmacophore model was generated based on HipHop and HYPOGEN method. A de novo compound library based on molecular fingerprints was constructed and virtually screened by the pharmacophore model. The results were further investigated by molecular docking study. The workflow successfully achieved potential ClpP inhibitors. It could be applied to design more novel potential ClpP inhibitors and provide theoretical basis for the further optimization of the hit compounds. PMID:25937012

  13. Modeling earthquake dynamics

    NASA Astrophysics Data System (ADS)

    Charpentier, Arthur; Durand, Marilou

    2015-07-01

    In this paper, we investigate questions arising in Parsons and Geist (Bull Seismol Soc Am 102:1-11, 2012). Pseudo causal models connecting magnitudes and waiting times are considered, through generalized regression. We do use conditional model (magnitude given previous waiting time, and conversely) as an extension to joint distribution model described in Nikoloulopoulos and Karlis (Environmetrics 19: 251-269, 2008). On the one hand, we fit a Pareto distribution for earthquake magnitudes, where the tail index is a function of waiting time following previous earthquake; on the other hand, waiting times are modeled using a Gamma or a Weibull distribution, where parameters are functions of the magnitude of the previous earthquake. We use those two models, alternatively, to generate the dynamics of earthquake occurrence, and to estimate the probability of occurrence of several earthquakes within a year or a decade.

  14. Mesoscale ocean dynamics modeling

    SciTech Connect

    mHolm, D.; Alber, M.; Bayly, B.; Camassa, R.; Choi, W.; Cockburn, B.; Jones, D.; Lifschitz, A.; Margolin, L.; Marsden, L.; Nadiga, B.; Poje, A.; Smolarkiewicz, P.; Levermore, D.

    1996-05-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The ocean is a very complex nonlinear system that exhibits turbulence on essentially all scales, multiple equilibria, and significant intrinsic variability. Modeling the ocean`s dynamics at mesoscales is of fundamental importance for long-time-scale climate predictions. A major goal of this project has been to coordinate, strengthen, and focus the efforts of applied mathematicians, computer scientists, computational physicists and engineers (at LANL and a consortium of Universities) in a joint effort addressing the issues in mesoscale ocean dynamics. The project combines expertise in the core competencies of high performance computing and theory of complex systems in a new way that has great potential for improving ocean models now running on the Connection Machines CM-200 and CM-5 and on the Cray T3D.

  15. Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa.

    PubMed

    Krovat, Eva M; Frühwirth, Karin H; Langer, Thierry

    2005-01-01

    Factor Xa inhibitors are innovative anticoagulant agents that provide a better safety/efficacy profile compared to other anticoagulative drugs. A chemical feature-based modeling approach was applied to identify crucial pharmacophore patterns from 3D crystal structures of inhibitors bound to human factor Xa (Pdb entries 1fjs, 1kns, 1eqz) using the software LIGANDSCOUT and CATALYST. The complex structures were selected regarding the criteria of high inhibitory potency (i.e. all ligands show K(i) values against factor Xa in the subnanomolar range) and good resolution (i.e. at least 2.2 A) in order to generate selective and high quality pharmacophore models. The resulting chemical-feature based hypotheses were used for virtual screening of commercial molecular databases such as the WDI database. Furthermore, a ligand-based molecular modeling approach was performed to obtain common-feature hypotheses that represent the relevant chemical interactions between 10 bioactive factor Xa inhibitors and the protein, respectively. In a next step a virtual combinatorial library was designed in order to generate new compounds with similar chemical and spatial properties as known inhibitors. The software tool ILIB DIVERSE was used for this procedure in order to provide new scaffolds of this group of anticoagulants. Finally we present the combination of these two techniques, hence virtual screening was performed with selective pharmacophore models in a focused virtual combinatorial database. De novo derived molecular scaffolds that were able to adequately satisfy the pharmacophore criteria are revealed and are promising templates for candidates for further development. PMID:15667140

  16. Model for macroevolutionary dynamics

    PubMed Central

    Maruvka, Yosef E.; Shnerb, Nadav M.; Kessler, David A.; Ricklefs, Robert E.

    2013-01-01

    The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21–87], which neglects extinction, or a simple birth–death (speciation–extinction) process. Here, we extend the more recent development of a generic, neutral speciation–extinction (of species)–origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom–sized taxonomic groups. The model’s predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution. PMID:23781101

  17. Contact dynamics math model

    NASA Technical Reports Server (NTRS)

    Glaese, John R.; Tobbe, Patrick A.

    1986-01-01

    The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

  18. New serotonin 5-HT(6) ligands from common feature pharmacophore hypotheses.

    PubMed

    Kim, Hye-Jung; Doddareddy, Munikumar Reddy; Choo, Hyunah; Cho, Yong Seo; No, Kyoung Tai; Park, Woo-Kyu; Pae, Ae Nim

    2008-01-01

    Serotonin 5-HT6 receptor antagonists are thought to play an important role in the treatment of psychiatry, Alzheimer's disease, and probably obesity. To find novel and potent 5-HT6 antagonists and to provide a new idea for drug design, we used a ligand-based pharmacophore to perform the virtual screening of a commercially available database. A three-dimensional common feature pharmacophore model was developed by using the HipHop program provided in Catalyst software and was used as a query for screening the database. A recursive partitioning (RP) model which can separate active and inactive compounds was used as a filtering system. Finally a sequential virtual screening procedure (SQSP) was conducted, wherein both the common feature pharmacophore and the RP model were used in succession to improve the results. Some of the hits were selected based on druglikeness, ADME properties, structural diversity, and synthetic accessibility for real biological evaluation. The best hit compound showed a significant IC50 value of 9.6 nM and can be used as a lead for further drug development. PMID:18044950

  19. Identification of potential dual agonists of FXR and TGR5 using e-pharmacophore based virtual screening.

    PubMed

    Sindhu, Thangaraj; Srinivasan, Pappu

    2015-05-01

    Farnesoid X receptor and Takeda G-protein-coupled receptor-5 are well known bile acid receptors and act as promising targets for the drug development and treatment of diabetes. Agonists of both the bile acid receptors increase insulin sensitivity and control glucose, lipids and bile acid homeostasis. The current study deals with the identification of novel dual agonists using ligand and structure-based virtual screening. Initially, an experimentally proven well-known dual agonist of FXR and TGR5, namely INT-767, was docked into the binding sites of FXR and TGR5 to determine the protein residues important for ligand binding. The docked complexes FXRINT-767 and TGR5INT-767 were used to generate e-pharmacophore hypotheses. Ligand-based virtual screening was carried out using the hypothetical e-pharmacophore model against the ChemBridge database. Further, structure-based virtual screening was performed with screened hits to find potential agonists of FXR and TGR5. A total of four best agonists were identified based on their affinity and mode of interactions with the receptors. The binding mode of these compounds with both receptors was analyzed in detail. Furthermore, molecular dynamics, ADME toxicity prediction, density functional theory and binding free energy calculations were carried out to rank the compounds. Based on the above analyses, the most potent compound, ChemBridge_9149693, was selected for further in vitro studies. The results of in vitro assays suggested that ChemBridge_9149693 is a potent and promising drug for the treatment of type II diabetes. Thus, the compound could be used for further drug design and development of dual agonists of FXR and TGR5. PMID:25787676

  20. Pharmacophore-based discovery of a novel cytosolic phospholipase A2α inhibitor

    PubMed Central

    Noha, Stefan M.; Jazzar, Bianca; Kuehnl, Susanne; Rollinger, Judith M.; Stuppner, Hermann; Schaible, Anja M.; Werz, Oliver; Wolber, Gerhard; Schuster, Daniela

    2012-01-01

    The release of arachidonic acid, a precursor in the production of prostaglandins and leukotrienes, is achieved by activity of the cytosolic phospholipase A2α (cPLA2α). Signaling mediated by this class of bioactive lipids, which are collectively referred to as eicosanoids, has numerous effects in physiological and pathological processes. Herein, we report the development of a ligand-based pharmacophore model and pharmacophore-based virtual screening of the National Cancer Institute (NCI) database, leading to the identification of 4-(hexadecyloxy)-3-(2-(hydroxyimino)-3-oxobutanamido)benzoic acid (NSC 119957) as cPLA2α inhibitor in cell-free and cell-based in vitro assays. PMID:22192589

  1. Identification of p38α MAP kinase inhibitors by pharmacophore based virtual screening.

    PubMed

    Gangwal, Rahul P; Das, Nihar R; Thanki, Kaushik; Damre, Mangesh V; Dhoke, Gaurao V; Sharma, Shyam S; Jain, Sanyog; Sangamwar, Abhay T

    2014-04-01

    The p38α mitogen-activated protein (MAP) kinase plays a vital role in treating many inflammatory diseases. In the present study, a combined ligand and structure based pharmacophore model was developed to identify potential DFG-in selective p38 MAP kinase inhibitors. Conformations of co-crystallised inhibitors were used in the development and validation of ligand and structure based pharmacophore modeling approached. The validated pharmacophore was utilized in database screening to identify potential hits. After Lipinski's rule of five filter and molecular docking analysis, nineteen hits were purchased and selected for in vitro analysis. The virtual hits exhibited promising activity against tumor necrosis factor-α (TNF-α) with 23-98% inhibition at 10μM concentration. Out of these seven compounds has shown potent inhibitory activity against p38 MAP kinase with IC50 values ranging from 12.97 to 223.5nM. In addition, the toxicity study against HepG2 cells was also carried out to confirm the safety profile of identified virtual hits. PMID:24473068

  2. Relativistic dynamical collapse model

    NASA Astrophysics Data System (ADS)

    Pearle, Philip

    2015-05-01

    A model is discussed where all operators are constructed from a quantum scalar field whose energy spectrum takes on all real values. The Schrödinger picture wave function depends upon space and time coordinates for each particle, as well as an inexorably increasing evolution parameter s which labels a foliation of spacelike hypersurfaces. The model is constructed to be manifestly Lorentz invariant in the interaction picture. Free particle states and interactions are discussed in this framework. Then, the formalism of the continuous spontaneous localization (CSL) theory of dynamical collapse is applied. The collapse-generating operator is chosen to be the particle number space-time density. Unlike previous relativistically invariant models, the vacuum state is not excited. The collapse dynamics depends upon two parameters, a parameter Λ which represents the collapse rate/volume and a scale factor ℓ. A common example of collapse dynamics, involving a clump of matter in a superposition of two locations, is analyzed. The collapse rate is shown to be identical to that of nonrelativistic CSL when the GRW-CSL choice of ℓ=a =1 0-5 cm , is made, along with Λ =λ /a3 (GRW-CSL choice λ =1 0-16s-1). The collapse rate is also satisfactory with the choice ℓ as the size of the Universe, with Λ =λ /ℓa2. Because the collapse narrows wave functions in space and time, it increases a particle's momentum and energy, altering its mass. It is shown that, with ℓ=a , the change of mass of a nucleon is unacceptably large but, when ℓ is the size of the Universe, the change of mass over the age of the Universe is acceptably small.

  3. Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

    PubMed Central

    Noor, Zainab; Afzal, Noreen; Rashid, Sajid

    2015-01-01

    Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy. PMID:26431201

  4. Energy-Based Pharmacophore and Three-Dimensional Quantitative Structure--Activity Relationship (3D-QSAR) Modeling Combined with Virtual Screening To Identify Novel Small-Molecule Inhibitors of Silent Mating-Type Information Regulation 2 Homologue 1 (SIRT1).

    PubMed

    Pulla, Venkat Koushik; Sriram, Dinavahi Saketh; Viswanadha, Srikant; Sriram, Dharmarajan; Yogeeswari, Perumal

    2016-01-25

    Silent mating-type information regulation 2 homologue 1 (SIRT1), being the homologous enzyme of silent information regulator-2 gene in yeast, has multifaceted functions. It deacetylates a wide range of histone and nonhistone proteins; hence, it has good therapeutic importance. SIRT1 was believed to be overexpressed in many cancers (prostate, colon) and inflammatory disorders (rheumatoid arthritis). Hence, designing inhibitors against SIRT1 could be considered valuable. Both structure-based and ligand-based drug design strategies were employed to design novel inhibitors utilizing high-throughput virtual screening of chemical databases. An energy-based pharmacophore was generated using the crystal structure of SIRT1 bound with a small molecule inhibitor and compared with a ligand-based pharmacophore model that showed four similar features. A three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed and validated to be employed in the virtual screening protocol. Among the designed compounds, Lead 17 emerged as a promising SIRT1 inhibitor with IC50 of 4.34 μM and, at nanomolar concentration (360 nM), attenuated the proliferation of prostate cancer cells (LnCAP). In addition, Lead 17 significantly reduced production of reactive oxygen species, thereby reducing pro inflammatory cytokines such as IL6 and TNF-α. Furthermore, the anti-inflammatory potential of the compound was ascertained using an animal paw inflammation model induced by carrageenan. Thus, the identified SIRT1 inhibitors could be considered as potent leads to treat both cancer and inflammation. PMID:26636371

  5. Lead generation using pharmacophore mapping and three-dimensional database searching: application to muscarinic M(3) receptor antagonists.

    PubMed

    Marriott, D P; Dougall, I G; Meghani, P; Liu, Y J; Flower, D R

    1999-08-26

    By using a pharmacophore model, a geometrical representation of the features necessary for molecules to show a particular biological activity, it is possible to search databases containing the 3D structures of molecules and identify novel compounds which may possess this activity. We describe our experiences of establishing a working 3D database system and its use in rational drug design. By using muscarinic M(3) receptor antagonists as an example, we show that it is possible to identify potent novel lead compounds using this approach. Pharmacophore generation based on the structures of known M(3) receptor antagonists, 3D database searching, and medium-throughput screening were used to identify candidate compounds. Three compounds were chosen to define the pharmacophore: a lung-selective M(3) antagonist patented by Pfizer and two Astra compounds which show affinity at the M(3) receptor. From these, a pharmacophore model was generated, using the program DISCO, and this was used subsequently to search a UNITY 3D database of proprietary compounds; 172 compounds were found to fit the pharmacophore. These compounds were then screened, and 1-[2-(2-(diethylamino)ethoxy)phenyl]-2-phenylethanone (pA(2) 6.67) was identified as the best hit, with N-[2-(piperidin-1-ylmethyl)cycohexyl]-2-propoxybenz amide (pA(2) 4. 83) and phenylcarbamic acid 2-(morpholin-4-ylmethyl)cyclohexyl ester (pA(2) 5.54) demonstrating lower activity. As well as its potency, 1-[2-(2-(diethylamino)ethoxy)phenyl]-2-phenylethanone is a simple structure with limited similarity to existing M(3) receptor antagonists. PMID:10464008

  6. Flupyradifurone (Sivanto™) and its novel butenolide pharmacophore: Structural considerations.

    PubMed

    Jeschke, Peter; Nauen, Ralf; Gutbrod, Oliver; Beck, Michael E; Matthiesen, Svend; Haas, Matthias; Velten, Robert

    2015-06-01

    Flupyradifurone (4-[(2,2-difluoroethyl)amino]-2(5H)-furanone), a member of the new class of butenolide insecticides, contains a novel bioactive scaffold as pharmacophore. It is very versatile in terms of application methods to a variety of crops, exhibits excellent and fast action against a broad spectrum of sucking pest insects including selected neonicotinoid resistant pest populations such as whiteflies and aphids expressing metabolic resistance mechanisms. As a partial agonist flupyradifurone reversibly binds to insect nicotinic acetylcholine receptors (nAChRs) and lacks metabolization by CYP6CM1, a cytochrome P450 over-expressed in cotton whiteflies resistant to imidacloprid and pymetrozine. The butenolide insecticides exhibit structure-activity relationships (SAR) that are different from other nAChR agonists such as the classes of neonicotinoids and sulfoximines. The paper briefly reviews the discovery of the butenolide insecticide flupyradifurone, its SAR differentiating it from established nAChR agonists and a molecular docking approach using the binding site model of CYP6CM1vQ of Bemisia tabaci known to confer metabolic resistance to neonicotinoid insecticides. PMID:26047109

  7. Thermal-dynamic modeling study

    NASA Technical Reports Server (NTRS)

    Ojalvo, I. U.

    1973-01-01

    Study provides basic information for designing models and conducting thermal-dynamic structural tests. Factors considered are development and interpretation of thermal-dynamic structural scaling laws; identification of major problem areas; and presentation of model fabrication, instrumentation, and test procedures.

  8. Chemometric design to explore pharmacophore features of BACE inhibitors for controlling Alzheimer's disease.

    PubMed

    Hossain, Tabassum; Mukherjee, Arup; Saha, Achintya

    2015-02-01

    The β-amyloid precursor protein cleavage enzyme (BACE) has been conceived to be an attractive therapeutic target to control Alzheimer's disease (AD). Validated ligand-based pharmacophore mapping was combined with 3D QSAR modeling approaches that include CoMFA, CoMSIA and HQSAR techniques to identify structural and physico-chemical requirements for a potential BACE inhibitor using a database containing 980 structurally diverse compounds, assembled from different reports. A structure-based docking technique was also used to validate the features obtained from the ligand-based models, which were further used to screen the database of compounds designed by a de novo approach. Contour maps of 3D QSAR models, CoMFA (R(2) = 0.880, se = 0.402, Q(2) = 0.596, Rpred(2) = 0.713,) and CoMSIA (R(2) = 0.903, se = 0.362, Q(2) = 0.578, Rpred(2) = 0.715), and a pharmacophore space model (R(2) = 0.833, rmsd = 1.578, Q(2) = 0.845, Rpred(2) = 0. 764) depict that the models are robust and provide an explanation of the important features such as steric, electrostatic, hydrophobic, positive ionization, hydrogen bond acceptor and donor properties, which play important roles for interaction with the receptor site cavity. The HQSAR study (R(2) = 0.823, se = 0.488, Q(2) = 0.823, Rpred(2) = 0.768) and de novo design, which generate new fragments, illustrated the important molecular fingerprints for inhibition. The docking study elucidated the important interactions between the amino acid residues (Gly11, Thr72, Asp228, Gly230, Thr231, Arg235) at the catalytic site of the receptor and the ligand, indicating the structural requirements of the inhibitors. The de novo designed molecules were further screened for ADMET properties, and ligand-receptor interactions of the top hits were analysed by molecular docking to explore pharmacophore features of BACE inhibitors. PMID:25435329

  9. Chemical function based pharmacophore generation of endothelin-A selective receptor antagonists.

    PubMed

    Funk, Oliver F; Kettmann, Viktor; Drimal, Jan; Langer, Thierry

    2004-05-20

    Both quantitative and qualitative chemical function based pharmacophore models of endothelin-A (ET(A)) selective receptor antagonists were generated by using the two algorithms HypoGen and HipHop, respectively, which are implemented in the Catalyst molecular modeling software. The input for HypoGen is a training set of 18 ET(A) antagonists exhibiting IC(50) values ranging between 0.19 nM and 67 microM. The best output hypothesis consists of five features: two hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI) function. The highest scoring Hip Hop model consists of six features: three hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI). It is the result of an input of three highly active, selective, and structurally diverse ET(A) antagonists. The predictive power of the quantitative model could be approved by using a test set of 30 compounds, whose activity values spread over 6 orders of magnitude. The two pharmacophores were tested according to their ability to extract known endothelin antagonists from the 3D molecular structure database of Derwent's World Drug Index. Thereby the main part of selective ET(A) antagonistic entries was detected by the two hypotheses. Furthermore, the pharmacophores were used to screen the Maybridge database. Six compounds were chosen from the output hit lists for in vitro testing of their ability to displace endothelin-1 from its receptor. Two of these are new potential lead compounds because they are structurally novel and exhibit satisfactory activity in the binding assay. PMID:15139753

  10. Recent Advances in Ligand-Based Drug Design: Relevance and Utility of the Conformationally Sampled Pharmacophore Approach

    PubMed Central

    Acharya, Chayan; Coop, Andrew; Polli, James E.; MacKerell, Alexander D.

    2010-01-01

    In the absence of three-dimensional (3D) structures of potential drug targets, ligand-based drug design is one of the popular approaches for drug discovery and lead optimization. 3D structure-activity relationships (3D QSAR) and pharmacophore modeling are the most important and widely used tools in ligand-based drug design that can provide crucial insights into the nature of the interactions between drug target and ligand molecule and provide predictive models suitable for lead compound optimization. This review article will briefly discuss the features and potential application of recent advances in ligand-based drug design, with emphasis on a detailed description of a novel 3D QSAR method based on the conformationally sample pharmacophore (CSP) approach (denoted CSP-SAR). In addition, data from a published study is used to compare the CSP-SAR approach to the Catalyst method, emphasizing the utility of the CSP approach for ligand-based model development. PMID:20807187

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

    PubMed

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

    2015-11-15

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

  12. PhDD: a new pharmacophore-based de novo design method of drug-like molecules combined with assessment of synthetic accessibility.

    PubMed

    Huang, Qi; Li, Lin-Li; Yang, Sheng-Yong

    2010-06-01

    This account describes a new pharmacophore-based de novo design method of drug-like molecules (PhDD). The method PhDD first generates a set of new molecules that completely conform to the requirements of a given pharmacophore model, followed by a series of assessments to the generated molecules, including assessments of drug-likeness, bioactivity, and synthetic accessibility. PhDD is tested on three typical examples, namely, pharmacophore hypotheses of histone deacetylase (HDAC), cyclin-dependent kinase 2 (CDK2) and HIV-1 integrase (IN) inhibitors. The test results demonstrate that PhDD is able to generate molecules with novel structures but having similar biological functions with existing inhibitors. The validity of PhDD together with its ability of assessing synthetic accessibility makes it a useful tool in rational drug design. PMID:20206562

  13. Dynamic modeling of power systems

    SciTech Connect

    Reed, M.; White, J.

    1995-12-01

    Morgantown Energy Technology Center`s (METC) Process and Project Engineering (P&PE) personnel continue to refine and modify dynamic modeling or simulations for advanced power systems. P&PE, supported by Gilbert/Commonwealth, Inc. (G/C), has adapted PC/TRAX commercial dynamic software to include equipment found in advanced power systems. PC/TRAX`s software contains the equations that describe the operation of standard power plant equipment such as gas turbines, feedwater pumps, and steam turbines. The METC team has incorporated customized dynamic models using Advanced Continuous Simulation Language (ACSL) code for pressurized circulating fluidized-bed combustors, carbonizers, and other components that are found in Advanced Pressurized Fluidized-Bed Combustion (APFBC) systems. A dynamic model of a commercial-size APFBC power plant was constructed in order to determine representative operating characteristics of the plant and to gain some insight into the best type of control system design. The dynamic model contains both process and control model components. This presentation covers development of a model used to describe the commercial APFBC power plant. Results of exercising the model to simulate plant performance are described and illustrated. Information gained during the APFBC study was applied to a dynamic model of a 1-1/2 generation PFBC system. Some initial results from this study are also presented.

  14. Pharmacophore development and screening for discovery of potential inhibitors of ADAMTS-4 for osteoarthritis therapy.

    PubMed

    Verma, Priyanka; Dalal, Krishna; Chopra, Madhu

    2016-08-01

    In the development of osteoarthritis, aggrecan degrades prior to cartilage destruction. Aggrecanase-1 (ADAMTS-4) is considered to be the major enzyme responsible for cleaving the Glu373-Ala374 bond in the interglobular domain of aggrecan in humans. Therefore, inhibitors of ADAMTS-4 have therapeutic potential in the treatment of osteoarthritis. In the present work, we developed a chemical feature based pharmacophore model of ADAMTS-4 inhibitors using the HipHop module within the Catalyst program package in order to elucidate the structure-activity relationship and to carry out in-silico screening. The Maybridge database was screened using Hypo1 as a 3D query, and the best-fit hits that followed Lipinski's rule of five were subsequently screened to select the compounds. The hit compounds were then docked into the active site of ADAMTS-4, and interactions were visualized to determine the potential lead molecules. After subjecting all of the hits to various screening and filtering processes, 13 compounds were finally evaluated for their in vitro inhibitory activities. This study resulted in the identification of two lead compounds with potent inhibitory effects on ADAMTS-4 activity, with IC50 values of 0.042 μM and 0.028 μM, respectively. These results provide insight into the pharmacophoric requirements for the development of more potent ADAMTS-4 inhibitors. Graphical Abstract The aggrecan-degrading metalloprotease ADAMTS-4 has been identified as a novel therapeutic target for osteoarthritis. In this work, we used HipHop-based pharmacophore modeling and virtual screening of the Maybridge database to identify novel ADAMTS-4 inhibitors. These novel lead compounds act as potent and specific inhibitors for the ADAMTS-4 enzyme and could have therapeutic potential in the treatment of OA. PMID:27401455

  15. SSME structural dynamic model development

    NASA Technical Reports Server (NTRS)

    Foley, M. J.; Tilley, D. M.; Welch, C. T.

    1983-01-01

    A mathematical model of the Space Shuttle Main Engine (SSME) as a complete assembly, with detailed emphasis on LOX and High Fuel Turbopumps is developed. The advantages of both complete engine dynamics, and high fidelity modeling are incorporated. Development of this model, some results, and projected applications are discussed.

  16. A novel potential therapeutic avenue for autism: Design, synthesis and pharmacophore generation of SSRIs with dual action

    PubMed Central

    Ghoneim, Ola M.; Ibrahim, Diaa A.; El-Deeb, Ibrahim M.; Lee, So Ha; Booth, Raymond G.

    2014-01-01

    Autism symptoms are currently modulated by Selective Serotonin Reuptake Inhibitors (SSRIs). SSRIs slow onset of action limits their efficiency. The established synergistic activity of SSRIs and 5HT1B/1D autoreceptors antagonists motivated us to incorporate SSRIs and 5HT1B/1D antagonists in one ‘hybrid’ molecule. A library of virtual ‘hybrid’ molecules was designed using the tethering technique. A pharmacophore model was generated derived from 16 structurally diverse SSRIs (Ki = 0.013–5000 nM) and used as 3D query. Compounds with fit values (≥2) were chosen for synthesis and subsequent in vitro biological evaluation. Our pharmacophore model is a promising milestone to a class of SSRIs with dual action. PMID:21982496

  17. COLD-SAT dynamic model

    NASA Astrophysics Data System (ADS)

    Adams, Neil S.; Bollenbacher, Gary

    1992-12-01

    This report discusses the development and underlying mathematics of a rigid-body computer model of a proposed cryogenic on-orbit liquid depot storage, acquisition, and transfer spacecraft (COLD-SAT). This model, referred to in this report as the COLD-SAT dynamic model, consists of both a trajectory model and an attitudinal model. All disturbance forces and torques expected to be significant for the actual COLD-SAT spacecraft are modeled to the required degree of accuracy. Control and experimental thrusters are modeled, as well as fluid slosh. The model also computes microgravity disturbance accelerations at any specified point in the spacecraft. The model was developed by using the Boeing EASY5 dynamic analysis package and will run on Apollo, Cray, and other computing platforms.

  18. COLD-SAT dynamic model

    NASA Technical Reports Server (NTRS)

    Adams, Neil S.; Bollenbacher, Gary

    1992-01-01

    This report discusses the development and underlying mathematics of a rigid-body computer model of a proposed cryogenic on-orbit liquid depot storage, acquisition, and transfer spacecraft (COLD-SAT). This model, referred to in this report as the COLD-SAT dynamic model, consists of both a trajectory model and an attitudinal model. All disturbance forces and torques expected to be significant for the actual COLD-SAT spacecraft are modeled to the required degree of accuracy. Control and experimental thrusters are modeled, as well as fluid slosh. The model also computes microgravity disturbance accelerations at any specified point in the spacecraft. The model was developed by using the Boeing EASY5 dynamic analysis package and will run on Apollo, Cray, and other computing platforms.

  19. Dynamic Modeling of ALS Systems

    NASA Technical Reports Server (NTRS)

    Jones, Harry

    2002-01-01

    The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.

  20. Aircraft Dynamic Modeling in Turbulence

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.; Cunninham, Kevin

    2012-01-01

    A method for accurately identifying aircraft dynamic models in turbulence was developed and demonstrated. The method uses orthogonal optimized multisine excitation inputs and an analytic method for enhancing signal-to-noise ratio for dynamic modeling in turbulence. A turbulence metric was developed to accurately characterize the turbulence level using flight measurements. The modeling technique was demonstrated in simulation, then applied to a subscale twin-engine jet transport aircraft in flight. Comparisons of modeling results obtained in turbulent air to results obtained in smooth air were used to demonstrate the effectiveness of the approach.

  1. Model describes subsea control dynamics

    SciTech Connect

    Not Available

    1988-02-01

    A mathematical model of the hydraulic control systems for subsea completions and their umbilicals has been developed and applied successfully to Jabiru and Challis field production projects in the Timor Sea. The model overcomes the limitations of conventional linear steady state models and yields for the hydraulic system an accurate description of its dynamic response, including the valve shut-in times and the pressure transients. Results of numerical simulations based on the model are in good agreement with measurements of the dynamic response of the tree valves and umbilicals made during land testing.

  2. Dynamical models of happiness.

    PubMed

    Sprott, J C

    2005-01-01

    A sequence of models for the time evolution of one's happiness in response to external events is described. These models with added nonlinearities can produce stable oscillations and chaos even without external events. Potential implications for psychotherapy and a personal approach to life are discussed. PMID:15629066

  3. Discovery of HIV-1 integrase inhibitors: pharmacophore mapping, virtual screening, molecular docking, synthesis, and biological evaluation.

    PubMed

    Bhatt, Hardik; Patel, Paresh; Pannecouque, Christophe

    2014-02-01

    HIV-1 integrase enzyme plays an important role in the life cycle of HIV and responsible for integration of virus into human genome. Here, both computational and synthetic approaches were used to design and synthesize newer HIV-1 integrase inhibitors. Pharmacophore mapping was performed on 20 chemically diverse molecules using DISCOtech, and refinement was carried out using GASP. Ten pharmacophore models were generated, and model 2, containing four features including two donor sites, one acceptor atom, and one hydrophobic region, was considered the best model as it has the highest fitness score. It was used as a query in NCI and Maybridge databases. Molecules having more than 99% Q(fit) value were used to design 30 molecules bearing pteridine ring and were docked on co-crystal structure of HIV-1 integrase enzyme. Among these, six molecules, showing good docking score compared with the reference standards, were synthesized by conventional as well as microwave-assisted methods. All compounds were characterized by physical and spectral data and evaluated for in vitro anti-HIV activity against the replication of HIV-1 (IIIB) in MT-4 cells. The used approach of molecular docking and anti-HIV activity data of designed molecules will provide significant insights to discover novel HIV-1 Integrase Inhibitors. PMID:23957390

  4. Pharmacophore Identification, Molecular Docking, Virtual Screening, and In Silico ADME Studies of Non-Nucleoside Reverse Transcriptase Inhibitors.

    PubMed

    Pirhadi, Somayeh; Ghasemi, Jahan B

    2012-12-01

    Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity and low toxicity in antiretroviral combination therapies used to treat HIV. In this study, chemical feature based pharmacophore models of different classes of NNRT inhibitors of HIV-1 have been developed. The best HypoRefine pharmacophore model, Hypo 1, which has the best correlation coefficient (0.95) and the lowest RMS (0.97), contains two hydrogen bond acceptors, one hydrophobic and one ring aromatic feature, as well as four excluded volumes. Hypo 1 was further validated by test set and Fischer validation method. The best pharmacophore model was then utilized as a 3D search query to perform a virtual screening to retrieve potential inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies by Libdock and Gold methods to refine the retrieved hits. Finally, 7 top ranked compounds based on Gold score fitness function were subjected to in silico ADME studies to investigate for compliance with the standard ranges. PMID:27476739

  5. Virtual screening using ligand-based pharmacophores for inhibitors of human tyrosyl-DNA phospodiesterase (hTdp1)

    PubMed Central

    Weidlich, Iwona E.; Dexheimer, Thomas; Marchand, Christophe; Antony, Smitha; Pommier, Yves; Nicklaus, Marc C.

    2012-01-01

    Human tyrosyl-DNA phosphodiesterase (hTdp1) inhibitors have become a major area of drug research and structure-based design since they have been shown to work synergistically with camptothecin (CPT) and selectively in cancer cells. The pharmacophore features of 14 hTdp1 inhibitors were used as a filter to screen the ChemNavigator iResearch Library of about 27 million purchasable samples. Docking of the inhibitors and hits obtained from virtual screening was performed into a structural model of hTdp1 based on a high resolution X-ray crystal structure of human Tdp1 in complex with vanadate, DNA and a human topoisomerase I (TopI)-derived peptide (PDB code: 1NOP). We present and discuss in some detail 46 compounds matching the three-dimensional arrangement of the pharmacophoric features. The presented novel chemotypes may provide new scaffolds for developing inhibitors of Tdp1. PMID:19963390

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

    PubMed

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

    2016-01-01

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

  7. Model of THz Magnetization Dynamics

    PubMed Central

    Bocklage, Lars

    2016-01-01

    Magnetization dynamics can be coherently controlled by THz laser excitation, which can be applied in ultrafast magnetization control and switching. Here, transient magnetization dynamics are calculated for excitation with THz magnetic field pulses. We use the ansatz of Smit and Beljers, to formulate dynamic properties of the magnetization via partial derivatives of the samples free energy density, and extend it to solve the Landau-Lifshitz-equation to obtain the THz transients of the magnetization. The model is used to determine the magnetization response to ultrafast multi- and single-cycle THz pulses. Control of the magnetization trajectory by utilizing the THz pulse shape and polarization is demonstrated. PMID:26956997

  8. One concept, three implementations of 3D pharmacophore-based virtual screening: distinct coverage of chemical search space.

    PubMed

    Spitzer, Gudrun M; Heiss, Mathias; Mangold, Martina; Markt, Patrick; Kirchmair, Johannes; Wolber, Gerhard; Liedl, Klaus R

    2010-07-26

    Feature-based pharmacophore modeling is a well-established concept to support early stage drug discovery, where large virtual databases are filtered for potential drug candidates. The concept is implemented in popular molecular modeling software, including Catalyst, Phase, and MOE. With these software tools we performed a comparative virtual screening campaign on HSP90 and FXIa, taken from the 'maximum unbiased validation' data set. Despite the straightforward concept that pharmacophores are based on, we observed an unexpectedly high degree of variation among the hit lists obtained. By harmonizing the pharmacophore feature definitions of the investigated approaches, the exclusion volume sphere settings, and the screening parameters, we have derived a rationale for the observed differences, providing insight on the strengths and weaknesses of these algorithms. Application of more than one of these software tools in parallel will result in a widened coverage of chemical space. This is not only rooted in the dissimilarity of feature definitions but also in different algorithmic search strategies. PMID:20583761

  9. Stochastic models of neuronal dynamics

    PubMed Central

    Harrison, L.M; David, O; Friston, K.J

    2005-01-01

    Cortical activity is the product of interactions among neuronal populations. Macroscopic electrophysiological phenomena are generated by these interactions. In principle, the mechanisms of these interactions afford constraints on biologically plausible models of electrophysiological responses. In other words, the macroscopic features of cortical activity can be modelled in terms of the microscopic behaviour of neurons. An evoked response potential (ERP) is the mean electrical potential measured from an electrode on the scalp, in response to some event. The purpose of this paper is to outline a population density approach to modelling ERPs. We propose a biologically plausible model of neuronal activity that enables the estimation of physiologically meaningful parameters from electrophysiological data. The model encompasses four basic characteristics of neuronal activity and organization: (i) neurons are dynamic units, (ii) driven by stochastic forces, (iii) organized into populations with similar biophysical properties and response characteristics and (iv) multiple populations interact to form functional networks. This leads to a formulation of population dynamics in terms of the Fokker–Planck equation. The solution of this equation is the temporal evolution of a probability density over state-space, representing the distribution of an ensemble of trajectories. Each trajectory corresponds to the changing state of a neuron. Measurements can be modelled by taking expectations over this density, e.g. mean membrane potential, firing rate or energy consumption per neuron. The key motivation behind our approach is that ERPs represent an average response over many neurons. This means it is sufficient to model the probability density over neurons, because this implicitly models their average state. Although the dynamics of each neuron can be highly stochastic, the dynamics of the density is not. This means we can use Bayesian inference and estimation tools that have

  10. Common Pharmacophore Identification Using Frequent Clique Detection Algorithm

    PubMed Central

    Podolyan, Yevgeniy; Karypis, George

    2008-01-01

    The knowledge of a pharmacophore, or the 3D arrangement of features in the biologically active molecule that is responsible for its pharmacological activity, can help in the search and design of a new or better drug acting upon the same or related target. In this paper we describe two new algorithms based on the frequent clique detection in the molecular graphs. The first algorithm mines all frequent cliques that are present in at least one of the conformers of each (or a portion of all) molecules. The second algorithm exploits the similarities among the different conformers of the same molecule and achieves an order of magnitude performance speedup compared to the first algorithm. Both algorithms are guaranteed to find all common pharmacophores in the dataset, which is confirmed by the validation on the set of molecules for which pharmacophores have been determined experimentally. In addition, these algorithms are able to scale to datasets with arbitrarily large number of conformers per molecule and identify multiple ligand binding modes or multiple binding sites of the target. PMID:19072298

  11. Tree Modeling and Dynamics Simulation

    NASA Astrophysics Data System (ADS)

    Tian-shuang, Fu; Yi-bing, Li; Dong-xu, Shen

    This paper introduces the theory about tree modeling and dynamic movements simulation in computer graphics. By comparing many methods we choose Geometry-based rendering as our method. The tree is decomposed into branches and leaves, under the rotation and quaternion methods we realize the tree animation and avoid the Gimbals Lock in Euler rotation. We take Orge 3D as render engine, which has good graphics programming ability. By the end we realize the tree modeling and dynamic movements simulation, achieve realistic visual quality with little computation cost.

  12. Pharmacophore generation of 2-substituted benzothiazoles as AdeABC efflux pump inhibitors in A. baumannii.

    PubMed

    Yilmaz, S; Altinkanat-Gelmez, G; Bolelli, K; Guneser-Merdan, D; Over-Hasdemir, M U; Yildiz, I; Aki-Yalcin, E; Yalcin, I

    2014-01-01

    RND family efflux pumps are important for multidrug resistance in Gram-negative bacteria. To date no efflux pump inhibitors for clinical use have been found, so developing the specific inhibitors of this pump system will be beneficial for the treatment of infections caused by these multidrug-resistant pathogens. A set of BSN-coded 2-substituted benzothiazoles were tested alone and in combination with ciprofloxacin (CIP) against the RND family efflux pump AdeABC overexpressor Acinetobacter baumannii SbMox-2 strain. The results indicated that the BSN compounds did not have antimicrobial activity when tested alone. However, if they were applied in combination with CIP, it was observed that the antibiotic had antimicrobial activity against the tested pathogen, possessing a minimum inhibitory concentration value that could be utilized in clinical treatment. A 3D-common features pharmacophore model was applied by using the HipHop method and the generated pharmacophore hypothesis revealed that the hydrogen bond acceptor property of nitrogen in the thiazole ring and the oxygen of the amide substituted at the second position of the benzothiazole ring system were significant for binding to the target protein. Moreover, three hydrophobic aromatic features were found to be essential for inhibitory activity. PMID:24905472

  13. Neuronal nicotinic receptor agonists: a multi-approach development of the pharmacophore.

    PubMed

    Nicolotti, O; Pellegrini-Calace, M; Carrieri, A; Altomare, C; Centeno, N B; Sanz, F; Carotti, A

    2001-09-01

    Based on the results obtained with different automated computational approaches as applied to the study of eleven high-affinity agonists of the neuronal nicotine acetylcholine receptor (nAChR), belonging to different chemical classes, new relevant features were detected which complement the existing pharmacophores. Convergent results from DISCO (Distance Comparison), QXP (Quick Explore), Catalyst/HipHop, and MIPSIM (Molecular Interaction Potential Similarity) allowed us to identify and locate, in a well defined spatial arrangement, three geometrically independent key structural features: (i) a positively charged nitrogen atom for ionic or hydrogen bond interactions, (ii) a lone pair of the pyridine nitrogen or a specific lone pair of a carbonyl oxygen, as a hydrogen bond acceptor, and (iii) a centre of a hydrophobic area generally occupied by aliphatic cycles. The pharmacophore presented herein, along with predictive 2D and 3D QSAR models recently developed in our group, could represent valuable computational tools for the design of new nAChR agonists having therapeutical potential. PMID:11776295

  14. Drug Repositioning and Pharmacophore Identification in the Discovery of Hookworm MIF Inhibitors

    SciTech Connect

    Y Cho; J Vermeire; J Merkel; L Leng; X Du; R Bucala; M Cappello; E Lolis

    2011-12-31

    The screening of bioactive compound libraries can be an effective approach for repositioning FDA-approved drugs or discovering new pharmacophores. Hookworms are blood-feeding, intestinal nematode parasites that infect up to 600 million people worldwide. Vaccination with recombinant Ancylostoma ceylanicum macrophage migration inhibitory factor (rAceMIF) provided partial protection from disease, thus establishing a 'proof-of-concept' for targeting AceMIF to prevent or treat infection. A high-throughput screen (HTS) against rAceMIF identified six AceMIF-specific inhibitors. A nonsteroidal anti-inflammatory drug (NSAID), sodium meclofenamate, could be tested in an animal model to assess the therapeutic efficacy in treating hookworm disease. Furosemide, an FDA-approved diuretic, exhibited submicromolar inhibition of rAceMIF tautomerase activity. Structure-activity relationships of a pharmacophore based on furosemide included one analog that binds similarly to the active site, yet does not inhibit the Na-K-Cl symporter (NKCC1) responsible for diuretic activity.

  15. Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening.

    PubMed

    Postigo, Matheus P; Guido, Rafael V C; Oliva, Glaucius; Castilho, Marcelo S; da R Pitta, Ivan; de Albuquerque, Julianna F C; Andricopulo, Adriano D

    2010-09-27

    Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma mansoni , one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure-activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 μM. The most potent inhibitors 7, 10, and 17 with IC(50) of 2, 18, and 38 μM, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis. PMID:20695479

  16. 3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance

    NASA Astrophysics Data System (ADS)

    Vilar, Santiago; Tatonetti, Nicholas P.; Hripcsak, George

    2015-03-01

    Adverse drugs events (ADEs) detection constitutes a considerable concern in patient safety and public health care. For this reason, it is important to develop methods that improve ADE signal detection in pharmacovigilance databases. Our objective is to apply 3D pharmacophoric similarity models to enhance ADE recognition in Offsides, a pharmacovigilance resource with drug-ADE associations extracted from the FDA Adverse Event Reporting System (FAERS). We developed a multi-ADE predictor implementing 3D drug similarity based on a pharmacophoric approach, with an ADE reference standard extracted from the SIDER database. The results showed that the application of our 3D multi-type ADE predictor to the pharmacovigilance data in Offsides improved ADE identification and generated enriched sets of drug-ADE signals. The global ROC curve for the Offsides ADE candidates ranked with the 3D similarity score showed an area of 0.7. The 3D predictor also allows the identification of the most similar drug that causes the ADE under study, which could provide hypotheses about mechanisms of action and ADE etiology. Our method is useful in drug development, screening potential adverse effects in experimental drugs, and in drug safety, applicable to the evaluation of ADE signals selected through pharmacovigilance data mining.

  17. Exploring the influence of the protein environment on metal-binding pharmacophores.

    PubMed

    Martin, David P; Blachly, Patrick G; McCammon, J Andrew; Cohen, Seth M

    2014-08-28

    The binding of a series of metal-binding pharmacophores (MBPs) related to the ligand 1-hydroxypyridine-2-(1H)-thione (1,2-HOPTO) in the active site of human carbonic anhydrase II (hCAII) has been investigated. The presence and/or position of a single methyl substituent drastically alters inhibitor potency and can result in coordination modes not observed in small-molecule model complexes. It is shown that this unexpected binding mode is the result of a steric clash between the methyl group and a highly ordered water network in the active site that is further stabilized by the formation of a hydrogen bond and favorable hydrophobic contacts. The affinity of MBPs is dependent on a large number of factors including donor atom identity, orientation, electrostatics, and van der Waals interactions. These results suggest that metal coordination by metalloenzyme inhibitors is a malleable interaction and that it is thus more appropriate to consider the metal-binding motif of these inhibitors as a pharmacophore rather than a "chelator". The rational design of inhibitors targeting metalloenzymes will benefit greatly from a deeper understanding of the interplay between the variety of forces governing the binding of MBPs to active site metal ions. PMID:25116076

  18. Pharmacophore based virtual screening, synthesis and SAR of novel inhibitors of Mycobacterium sulfotransferase.

    PubMed

    Saha, Rikta; Tanwar, Omprakash; Alam, M Mumtaz; Zaman, M S; Khan, Shah A; Akhter, Mymoona

    2015-02-01

    A planned 3D-pharmacophore mapping was carried out on the basis of chemical features associated with known Stf0 inhibitors. Four models (model 1-4) were obtained after GASP (Genetic Algorithm Similarity Program) refinement of seven models (D-1 to D-7) generated by using DISCOtech. The selected GASP model-1 has two hydrogen bond acceptor, two hydrogen bond donor and four hydrophobic points. This model was used for virtual screening (VS) of large public databases along with in house generated knowledge base database. VS followed by docking of selected compounds on Stf0 active site was carried and pose analysis done. Seven hits were identified after all the computational studies, of which 2 hits were synthesized along with their analogs and evaluated for antitubercular activity. IH-45 was found promising after in vitro assay. PMID:25541388

  19. Global/Local Dynamic Models

    SciTech Connect

    Pfeffer, A; Das, S; Lawless, D; Ng, B

    2006-10-10

    Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.

  20. Modeling tumor evolutionary dynamics

    PubMed Central

    Stransky, Beatriz; de Souza, Sandro J.

    2013-01-01

    Tumorigenesis can be seen as an evolutionary process, in which the transformation of a normal cell into a tumor cell involves a number of limiting genetic and epigenetic events, occurring in a series of discrete stages. However, not all mutations in a cell are directly involved in cancer development and it is likely that most of them (passenger mutations) do not contribute in any way to tumorigenesis. Moreover, the process of tumor evolution is punctuated by selection of advantageous (driver) mutations and clonal expansions. Regarding these driver mutations, it is uncertain how many limiting events are required and/or sufficient to promote a tumorigenic process or what are the values associated with the adaptive advantage of different driver mutations. In spite of the availability of high-quality cancer data, several assumptions about the mechanistic process of cancer initiation and development remain largely untested, both mathematically and statistically. Here we review the development of recent mathematical/computational models and discuss their impact in the field of tumor biology. PMID:23420281

  1. Observability in dynamic evolutionary models.

    PubMed

    López, I; Gámez, M; Carreño, R

    2004-02-01

    In the paper observability problems are considered in basic dynamic evolutionary models for sexual and asexual populations. Observability means that from the (partial) knowledge of certain phenotypic characteristics the whole evolutionary process can be uniquely recovered. Sufficient conditions are given to guarantee observability for both sexual and asexual populations near an evolutionarily stable state. PMID:15013222

  2. Enhancing specificity and sensitivity of pharmacophore-based virtual screening by incorporating chemical and shape features--a case study of HIV protease inhibitors.

    PubMed

    Pandit, Deepangi; So, Sung-Sau; Sun, Hongmao

    2006-01-01

    Virtual screening (VS), if applied appropriately, could significantly shorten the hit identification and hit-to-lead processes in drug discovery. Recently, the version of VS that is based upon similarity to a pharmacophore has received increased attention. This is due to two major factors: first, the public availability of the ZINC1 conformational database has provided a large selection pool with high-quality and purchasable small molecules; second, new technology has enabled a more accurate and flexible definition of pharmacophore models coupled with an efficient search speed. The major goal of this study was to achieve improved specificity and sensitivity of pharmacophore-based VS by optimizing the variables used to generate conformations of small molecules and those used to construct pharmacophore models from known inhibitors or from inhibitor-protein complex structures. By using human immunodeficiency virus protease and its inhibitors (PIs) as a case study, the impact of the key variables, including the selection of chemical features, involvement of excluded volumes (EV), the tolerance radius of excluded volumes, energy windows, and the maximum number of conformers in conformation generation, was explored. Protein flexibility was simulated by adjusting the sizes of EV. Our best pharmacophore model, combining both chemical features and excluded volumes, was able to correctly identify 60 out of 75 structurally diverse known PIs, while misclassifying only 5 out of 75 similar compounds that are not inhibitors. To evaluate the specificity of the model, 1193 oral drugs on the market were screened, and 25 original hits were identified, including 5 out of 6 known PI drugs. PMID:16711743

  3. Conceptual dynamical models for turbulence.

    PubMed

    Majda, Andrew J; Lee, Yoonsang

    2014-05-01

    Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave-mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605

  4. Conceptual dynamical models for turbulence

    PubMed Central

    Majda, Andrew J.; Lee, Yoonsang

    2014-01-01

    Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave–mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605

  5. Modelling the mechanoreceptor's dynamic behaviour.

    PubMed

    Song, Zhuoyi; Banks, Robert W; Bewick, Guy S

    2015-08-01

    All sensory receptors adapt, i.e. they constantly adjust their sensitivity to external stimuli to match the current demands of the natural environment. Electrophysiological responses of sensory receptors from widely different modalities seem to exhibit common features related to adaptation, and these features can be used to examine the underlying sensory transduction mechanisms. Among the principal senses, mechanosensation remains the least understood at the cellular level. To gain greater insights into mechanosensory signalling, we investigated if mechanosensation displayed adaptive dynamics that could be explained by similar biophysical mechanisms in other sensory modalities. To do this, we adapted a fly photoreceptor model to describe the primary transduction process for a stretch-sensitive mechanoreceptor, taking into account the viscoelastic properties of the accessory muscle fibres and the biophysical properties of known mechanosensitive channels (MSCs). The model's output is in remarkable agreement with the electrical properties of a primary ending in an isolated decapsulated spindle; ramp-and-hold stretch evokes a characteristic pattern of potential change, consisting of a large dynamic depolarization during the ramp phase and a smaller static depolarization during the hold phase. The initial dynamic component is likely to be caused by a combination of the mechanical properties of the muscle fibres and a refractory state in the MSCs. Consistent with the literature, the current model predicts that the dynamic component is due to a rapid stress increase during the ramp. More novel predictions from the model are the mechanisms to explain the initial peak in the dynamic component. At the onset of the ramp, all MSCs are sensitive to external stimuli, but as they become refractory (inactivated), fewer MSCs are able to respond to the continuous stretch, causing a sharp decrease after the peak response. The same mechanism could contribute a faster component in the

  6. Quantitative conformationally sampled pharmacophore for delta opioid ligands: reevaluation of hydrophobic moieties essential for biological activity.

    PubMed

    Bernard, Denzil; Coop, Andrew; MacKerell, Alexander D

    2007-04-19

    Recent studies have indicated several therapeutic applications for delta opioid agonists and antagonists. To exploit the therapeutic potential of delta opioids developing a structural basis for the activity of ligands at the delta opioid receptor is essential. The conformationally sampled pharmacophore (CSP) method (Bernard et al. J. Am. Chem. Soc. 2003, 125, 3103-3107) is extended here to obtain quantitative models of delta opioid ligand efficacy and affinity. Quantification is performed via overlap integrals of the conformational space sampled by ligands with respect to a reference compound. Iterative refinement of the CSP model identified hydrophobic groups other than the traditional phenylalanine residues as important for efficacy and affinity in DSLET and ICI 174 864. The obtained models for a structurally diverse set of peptidic and nonpeptidic delta opioid ligands offer good predictions with R2 values>0.9, and the predicted efficacy for a set of test compounds was consistent with the experimental values. PMID:17367120

  7. Modelling MIZ dynamics in a global model

    NASA Astrophysics Data System (ADS)

    Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

    2016-04-01

    Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

  8. Computational modeling toward understanding agonist binding on dopamine 3.

    PubMed

    Zhao, Yaxue; Lu, Xuefeng; Yang, Chao-Yie; Huang, Zhimin; Fu, Wei; Hou, Tingjun; Zhang, Jian

    2010-09-27

    The dopamine 3 (D3) receptor is a promising therapeutic target for the treatment of nervous system disorders, such as Parkinson's disease, and current research interests primarily focus on the discovery/design of potent D3 agonists. Herein, a well-designed computational protocol, which combines pharmacophore identification, homology modeling, molecular docking, and molecular dynamics (MD) simulations, was employed to understand the agonist binding on D3 aiming to provide insights into the development of novel potent D3 agonists. We (1) identified the chemical features required in effective D3 agonists by pharmacophore modeling based upon 18 known diverse D3 agonists; (2) constructed the three-dimensional (3D) structure of D3 based on homology modeling and the pharmacophore hypothesis; (3) identified the binding modes of the agonists to D3 by the correlation between the predicted binding free energies and the experimental values; and (4) investigated the induced fit of D3 upon agonist binding through MD simulations. The pharmacophore models of the D3 agonists and the 3D structure of D3 can be used for either ligand- or receptor-based drug design. Furthermore, the MD simulations further give the insight that the long and flexible EL2 acts as a "door" for agonist binding, and the "ionic lock" at the bottom of TM3 and TM6 is essential to transduce the activation signal. PMID:20695484

  9. On whole Abelian model dynamics

    SciTech Connect

    Chauca, J.; Doria, R.

    2012-09-24

    Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.

  10. Exploration of Novel Inhibitors for Bruton’s Tyrosine Kinase by 3D QSAR Modeling and Molecular Dynamics Simulation

    PubMed Central

    Choi, Light; Woo Lee, Keun

    2016-01-01

    Bruton’s tyrosine kinase (BTK) is a cytoplasmic, non-receptor tyrosine kinase which is expressed in most of the hematopoietic cells and plays an important role in many cellular signaling pathways. B cell malignancies are dependent on BCR signaling, thus making BTK an efficient therapeutic target. Over the last few years, significant efforts have been made in order to develop BTK inhibitors to treat B-cell malignancies, and autoimmunity or allergy/hypersensitivity but limited success has been achieved. Here in this study, 3D QSAR pharmacophore models were generated for Btk based on known IC50 values and experimental energy scores with extensive validations. The five features pharmacophore model, Hypo1, includes one hydrogen bond acceptor lipid, one hydrogen bond donor, and three hydrophobic features, which has the highest correlation coefficient (0.98), cost difference (112.87), and low RMS (1.68). It was further validated by the Fisher’s randomization method and test set. The well validated Hypo1 was used as a 3D query to search novel Btk inhibitors with different chemical scaffold using high throughput virtual screening technique. The screened compounds were further sorted by applying ADMET properties, Lipinski’s rule of five and molecular docking studies to refine the retrieved hits. Furthermore, molecular dynamic simulation was employed to study the stability of docked conformation and to investigate the binding interactions in detail. Several important hydrogen bonds with Btk were revealed, which includes the gatekeeper residues Glu475 and Met 477 at the hinge region. Overall, this study suggests that the proposed hits may be more effective inhibitors for cancer and autoimmune therapy. PMID:26784025

  11. Rational design of biaryl pharmacophore inserted noscapine derivatives as potent tubulin binding anticancer agents.

    PubMed

    Santoshi, Seneha; Manchukonda, Naresh Kumar; Suri, Charu; Sharma, Manya; Sridhar, Balasubramanian; Joseph, Silja; Lopus, Manu; Kantevari, Srinivas; Baitharu, Iswar; Naik, Pradeep Kumar

    2015-03-01

    We have strategically designed a series of noscapine derivatives by inserting biaryl pharmacophore (a major structural constituent of many of the microtubule-targeting natural anticancer compounds) onto the scaffold structure of noscapine. Molecular interaction of these derivatives with α,β-tubulin heterodimer was investigated by molecular docking, molecular dynamics simulation, and binding free energy calculation. The predictive binding affinity indicates that the newly designed noscapinoids bind to tubulin with a greater affinity. The predictive binding free energy (ΔG(bind, pred)) of these derivatives (ranging from -5.568 to -5.970 kcal/mol) based on linear interaction energy (LIE) method with a surface generalized Born (SGB) continuum solvation model showed improved binding affinity with tubulin compared to the lead compound, natural α-noscapine (-5.505 kcal/mol). Guided by the computational findings, these new biaryl type α-noscapine congeners were synthesized from 9-bromo-α-noscapine using optimized Suzuki reaction conditions for further experimental evaluation. The derivatives showed improved inhibition of the proliferation of human breast cancer cells (MCF-7), human cervical cancer cells (HeLa) and human lung adenocarcinoma cells (A549), compared to natural noscapine. The cell cycle analysis in MCF-7 further revealed that these compounds alter the cell cycle profile and cause mitotic arrest at G2/M phase more strongly than noscapine. Tubulin binding assay revealed higher binding affinity to tubulin, as suggested by dissociation constant (Kd) of 126 ± 5.0 µM for 5a, 107 ± 5.0 µM for 5c, 70 ± 4.0 µM for 5d, and 68 ± 6.0 µM for 5e compared to noscapine (Kd of 152 ± 1.0 µM). In fact, the experimentally determined value of ΔG(bind, expt) (calculated from the Kd value) are consistent with the predicted value of ΔG(bind, pred) calculated based on LIE-SGB. Based on these results, one of the derivative 5e of this series was used for further

  12. Evolution models with extremal dynamics.

    PubMed

    Kärenlampi, Petri P

    2016-08-01

    The random-neighbor version of the Bak-Sneppen biological evolution model is reproduced, along with an analogous model of random replicators, the latter eventually experiencing topology changes. In the absence of topology changes, both types of models self-organize to a critical state. Species extinctions in the replicator system degenerates the self-organization to a random walk, as does vanishing of species interaction for the BS-model. A replicator model with speciation is introduced, experiencing dramatic topology changes. It produces a variety of features, but self-organizes to a possibly critical state only in a few special cases. Speciation-extinction dynamics interfering with self-organization, biological macroevolution probably is not a self-organized critical system. PMID:27626090

  13. Dynamical model of brushite precipitation

    NASA Astrophysics Data System (ADS)

    Oliveira, Cristina; Georgieva, Petia; Rocha, Fernando; Ferreira, António; Feyo de Azevedo, Sebastião

    2007-07-01

    The objectives of this work are twofold. From academic point of view the aim is to build a dynamical macro model to fit the material balance and explain the main kinetic mechanisms that govern the transformation of the hydroxyapatite (HAP) into brushite and the growth of brushite, based on laboratory experiments and collected database. From practical point of view, the aim is to design a reliable process simulator that can be easily imbedded in industrial software for model driven monitoring, optimization and control purposes. Based upon a databank of laboratory measurements of the calcium concentration in solution (on-line) and the particle size distribution (off-line) a reliable dynamical model of the dual nature of brushite particle formation for a range of initial concentrations of the reagents was derived as a system of ordinary differential equations of time. The performance of the model is tested with respect to the predicted evolution of mass of calcium in solution and the average (in mass) particle size along time. Results obtained demonstrate a good agreement between the model time trajectories and the available experimental data for a number of different initial concentrations of reagents.

  14. Towards a Dynamic DES model

    NASA Astrophysics Data System (ADS)

    Subbareddy, Pramod; Candler, Graham

    2009-11-01

    Hybrid RANS/LES methods are being increasingly used for turbulent flow simulations in complex geometries. Spalart's detached eddy simulation (DES) model is one of the more popular ones. We are interested in examining the behavior of the Spalart-Allmaras (S-A) Detached Eddy Simulation (DES) model in its ``LES mode.'' The role of the near-wall functions present in the equations is analyzed and an explicit analogy between the S-A and a one-equation LES model based on the sub-grid kinetic energy is presented. A dynamic version of the S-A DES model is proposed based on this connection. Validation studies and results from DES and LES applications will be presented and the effect of the proposed modification will be discussed.

  15. Discovery and pharmacophore studies of novel pyrazole-based anti-melanoma agents.

    PubMed

    Li, Qing-Shan; Lü, Xian-Hai; Yang, Yang; Ruan, Ban-Feng; Yao, Ri-Sheng; Liao, Chen-Zhong

    2015-01-01

    Due to the rising incidence and lack of effective treatments, malignant melanoma is the most dangerous form of skin cancer, so that new treatment strategies are urgently needed. Several recent developments indicate that the V600E mutant BRAF (BRAF(V600E) ) is a validated target for antimelanoma-drug development. Based on in silico screening results, a series of novel pyrazole derivatives has been designed, synthesized, and evaluated in vitro for their inhibitory activities against BRAF(V600E) melanoma cells. Compound 3d exhibited the most potent inhibitory activity with an IC50 value of 0.63 μM for BRAF(V600E) and a GI50 value of 0.61 μM for mutant BRAF-dependent cells. Furthermore, the QSAR modeling and the docking simulation of inhibitor analogs provide important pharmacophore clues for further structural optimization. PMID:25641840

  16. Discovery of Potent Succinate-Ubiquinone Oxidoreductase Inhibitors via Pharmacophore-linked Fragment Virtual Screening Approach.

    PubMed

    Xiong, Li; Zhu, Xiao-Lei; Gao, Hua-Wei; Fu, Yu; Hu, Sheng-Quan; Jiang, Li-Na; Yang, Wen-Chao; Yang, Guang-Fu

    2016-06-22

    Succinate-ubiquinone oxidoreductase (SQR) is an attractive target for fungicide discovery. Herein, we report the discovery of novel SQR inhibitors using a pharmacophore-linked fragment virtual screening approach, a new drug design method developed in our laboratory. Among newly designed compounds, compound 9s was identified as the most potent inhibitor with a Ki value of 34 nM against porcine SQR, displaying approximately 10-fold higher potency than that of the commercial control penthiopyrad. Further inhibitory kinetics studies revealed that compound 9s is a noncompetitive inhibitor with respect to the substrate cytochrome c and DCIP. Interestingly, compounds 8a, 9h, 9j, and 9k exhibited good in vivo preventive effects against Rhizoctonia solani. The results obtained from molecular modeling showed that the orientation of the R(2) group had a significant effect on binding with the protein. PMID:27225833

  17. Modeling Wildfire Incident Complexity Dynamics

    PubMed Central

    Thompson, Matthew P.

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014

  18. USRCAT: real-time ultrafast shape recognition with pharmacophoric constraints

    PubMed Central

    2012-01-01

    Background Ligand-based virtual screening using molecular shape is an important tool for researchers who wish to find novel chemical scaffolds in compound libraries. The Ultrafast Shape Recognition (USR) algorithm is capable of screening millions of compounds and is therefore suitable for usage in a web service. The algorithm however is agnostic of atom types and cannot discriminate compounds with similar shape but distinct pharmacophoric features. To solve this problem, an extension of USR called USRCAT, has been developed that includes pharmacophoric information whilst retaining the performance benefits of the original method. Results The USRCAT extension is shown to outperform the traditional USR method in a retrospective virtual screening benchmark. Also, a relational database implementation is described that is capable of screening a million conformers in milliseconds and allows the inclusion of complex query parameters. Conclusions USRCAT provides a solution to the lack of atom type information in the USR algorithm. Researchers, particularly those with only limited resources, who wish to use ligand-based virtual screening in order to discover new hits, will benefit the most. Online chemical databases that offer a shape-based similarity method might also find advantage in using USRCAT due to its accuracy and performance. The source code is freely available and can easily be modified to fit specific needs. PMID:23131020

  19. Data modeling of network dynamics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad

    2004-01-01

    This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.

  20. Dolastatin 11 conformations, analogues and pharmacophore.

    PubMed

    Ali, Md Ahad; Bates, Robert B; Crane, Zackary D; Dicus, Christopher W; Gramme, Michelle R; Hamel, Ernest; Marcischak, Jacob; Martinez, David S; McClure, Kelly J; Nakkiew, Pichaya; Pettit, George R; Stessman, Chad C; Sufi, Bilal A; Yarick, Gayle V

    2005-07-01

    Twenty analogues of the natural antitumor agent dolastatin 11, including majusculamide C, were synthesized and tested for cytotoxicity against human cancer cells and stimulation of actin polymerization. Only analogues containing the 30-membered ring were active. Molecular modeling and NMR evidence showed the low-energy conformations. The amide bonds are all trans except for the one between the Tyr and Val units, which is cis. Since an analogue restricted to negative 2-3-4-5 angles stimulated actin polymerization but was inactive in cells, the binding conformation (most likely the lowest-energy conformation in water) has a negative 2-3-4-5 angle, whereas a conformation with a positive 2-3-4-5 angle (most likely the lowest energy conformation in chloroform) goes through cell walls. The highly active R alcohol from borohydride reduction of dolastatin 11 is a candidate for conversion to prodrugs. PMID:15878670

  1. Opinion dynamics model with weighted influence: Exit probability and dynamics

    NASA Astrophysics Data System (ADS)

    Biswas, Soham; Sinha, Suman; Sen, Parongama

    2013-08-01

    We introduce a stochastic model of binary opinion dynamics in which the opinions are determined by the size of the neighboring domains. The exit probability here shows a step function behavior, indicating the existence of a separatrix distinguishing two different regions of basin of attraction. This behavior, in one dimension, is in contrast to other well known opinion dynamics models where no such behavior has been observed so far. The coarsening study of the model also yields novel exponent values. A lower value of persistence exponent is obtained in the present model, which involves stochastic dynamics, when compared to that in a similar type of model with deterministic dynamics. This apparently counterintuitive result is justified using further analysis. Based on these results, it is concluded that the proposed model belongs to a unique dynamical class.

  2. COLD-SAT Dynamic Model Computer Code

    NASA Technical Reports Server (NTRS)

    Bollenbacher, G.; Adams, N. S.

    1995-01-01

    COLD-SAT Dynamic Model (CSDM) computer code implements six-degree-of-freedom, rigid-body mathematical model for simulation of spacecraft in orbit around Earth. Investigates flow dynamics and thermodynamics of subcritical cryogenic fluids in microgravity. Consists of three parts: translation model, rotation model, and slosh model. Written in FORTRAN 77.

  3. Dynamics of the standard model

    SciTech Connect

    Donoghue, J.F.; Golowich, E.; Holstein, B.R.

    1992-01-01

    Given the remarkable successes of the standard model, it is appropriate that books in the field no longer dwell on the development of our current understanding of high-energy physics but rather present the world as we now know it. Dynamics of the Standard Model by Donoghue, Golowich, and Holstein takes just this approach. Instead of showing the confusion of the 60s and 70s, the authors present the enlightenment of the 80s. They start by describing the basic features and structure of the standard model and then concentrate on the techniques whereby the model can be applied to the physical world, connecting the theory to the experimental results that are the source of its success. Because they do not dwell on ancient (pre-1980) history, the authors of this book are able to go into much more depth in describing how the model can be tied to experiment, and much of the information presented has been accessible previously only in journal articles in a highly technical form. Though all of the authors are card-carrying theorists they go out of their way to stress applications and phenomenology and to show the reader how real-life calculations of use to experimentalists are done and can be applied to physical situations: what assumptions are made in doing them and how well they work. This is of great value both to the experimentalist seeking a deeper understanding of how the standard model can be connected to data and to the theorist wanting to see how detailed the phenomenological predictions of the standard model are and how well the model works. Furthermore, the authors constantly go beyond the lowest-order predictions of the standard model to discuss the corrections to it, as well as higher-order processes, some of which are now experimentally accessible and others of which will take well into the decade to uncover.

  4. In Silico Identification and Evaluation of Leads for the Simultaneous Inhibition of Protease and Helicase Activities of HCV NS3/4A Protease Using Complex Based Pharmacophore Mapping and Virtual Screening

    PubMed Central

    Wadood, Abdul; Riaz, Muhammad; Uddin, Reaz; ul-Haq, Zaheer

    2014-01-01

    Hepatitis C virus (HCV) infection is an alarming and growing threat to public health. The present treatment gives limited efficacy and is poorly tolerated, recommending the urgent medical demand for novel therapeutics. NS3/4A protease is a significant emerging target for the treatment of HCV infection. This work reports the complex-based pharmacophore modeling to find out the important pharmacophoric features essential for the inhibition of both protease and helicase activity of NS3/4A protein of HCV. A seven featured pharmacophore model of HCV NS3/4A protease was developed from the crystal structure of NS3/4A protease in complex with a macrocyclic inhibitor interacting with both protease and helicase sites residues via MOE pharmacophore constructing tool. It consists of four hydrogen bond acceptors (Acc), one hydrophobic (Hyd), one for lone pair or active hydrogen (Atom L) and a heavy atom feature (Atom Q). The generated pharmacophore model was validated by a test database of seventy known inhibitors containing 55 active and 15 inactive/least active compounds. The validated pharmacophore model was used to virtually screen the ChemBridge database. As a result of screening 1009 hits were retrieved and were subjected to filtering by Lipinski’s rule of five on the basis of which 786 hits were selected for further assessment using molecular docking studies. Finally, 15 hits of different scaffolds having interactions with important active site residues were predicted as lead candidates. These candidates having unique scaffolds have a strong likelihood to act as further starting points in the development of novel and potent NS3/4A protease inhibitors. PMID:24551230

  5. Dynamical modeling of tidal streams

    SciTech Connect

    Bovy, Jo

    2014-11-01

    I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

  6. Dynamical Modeling of Tidal Streams

    NASA Astrophysics Data System (ADS)

    Bovy, Jo

    2014-11-01

    I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its "track") in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of "orphan" streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

  7. Dynamically Evolving Models of Clusters

    NASA Astrophysics Data System (ADS)

    Bode, Paul W.; Berrington, Robert C.; Cohn, Haldan N.; Lugger, Phyllis M.

    1993-12-01

    An N-body method, with up to N=10(5) particles, is used to simulate the dynamical evolution of clusters of galaxies. Each galaxy is represented as an extended structure containing many particles, and the gravitational potential arises from the particles alone. The clusters initially contain 50 or 100 galaxies with masses distributed according to a Schechter function. Mass is apportioned between the galaxies and a smoothly distributed common group halo, or intra-cluster background. The fraction of the total cluster mass initially in this background is varied from 50% to 90%. The models begin in a virialized state. We will be presenting a videotape which contains animations of a number of these models. The animations show important physical processes, such as stripping, merging, and dynamical friction, as they take place, thus allowing one to observe the interplay of these processes in the global evolution of the system. When the galaxies have substantial dark halos (background mass fraction <=75%) a large, centrally located merger remnant is created. The galaxy number density profile around this dominant member becomes cusped, approaching an isothermal distribution. At the same time, the number of multiple nuclei increases. Comparing the 50-galaxy models to MKW/AWM clusters, the values of Delta M12 and the peculiar velocities of the first-ranked galaxies are best fit by a mix of model ages in the range 8--11 Gyr. The growth in luminosity of the first-ranked galaxy during this amount of time is consistent only with weak cannibalism.

  8. Polygamain, a New Microtubule Depolymerizing Agent That Occupies a Unique Pharmacophore in the Colchicine Site

    PubMed Central

    Hartley, R. M.; Peng, J.; Fest, G. A.; Dakshanamurthy, S.; Frantz, D. E.; Brown, M. L.

    2012-01-01

    Bioassay-guided fractionation was used to isolate the lignan polygamain as the microtubule-active constituent in the crude extract of the Mountain torchwood, Amyris madrensis. Similar to the effects of the crude plant extract, polygamain caused dose-dependent loss of cellular microtubules and the formation of aberrant mitotic spindles that led to G2/M arrest. Polygamain has potent antiproliferative activities against a wide range of cancer cell lines, with an average IC50 of 52.7 nM. Clonogenic studies indicate that polygamain effectively inhibits PC-3 colony formation and has excellent cellular persistence after washout. In addition, polygamain is able to circumvent two clinically relevant mechanisms of drug resistance, the expression of P-glycoprotein and the βIII isotype of tubulin. Studies with purified tubulin show that polygamain inhibits the rate and extent of purified tubulin assembly and displaces colchicine, indicating a direct interaction of polygamain within the colchicine binding site on tubulin. Polygamain has structural similarities to podophyllotoxin, and molecular modeling simulations were conducted to identify the potential orientations of these compounds within the colchicine binding site. These studies suggest that the benzodioxole group of polygamain occupies space similar to the trimethoxyphenyl group of podophyllotoxin but with distinct interactions within the hydrophobic pocket. Our results identify polygamain as a new microtubule destabilizer that seems to occupy a unique pharmacophore within the colchicine site of tubulin. This new pharmacophore will be used to design new colchicine site compounds that might provide advantages over the current agents. PMID:22169850

  9. Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification.

    PubMed

    Islam, Md Ataul; Pillay, Tahir S

    2015-03-01

    Pharmacoinformatics approaches are widely used in the field of drug discovery as it saves time, investment and animal sacrifice. In the present study, pharmacore-based virtual screening was adopted to identify potential HIV-protease ligands as anti-HIV agents. Pharmacophore is the 3D orientation and spatial arrangement of functional groups that are critical for binding at the active site cavity. Virtual screening retrieves potential hit molecules from databases based on imposed criteria. A set of 30 compounds were selected with inhibition constant as training set from 129 compounds of dataset set and subsequently the pharmacophore model was developed. The selected best model consists of hydrogen bond acceptor and donor, hydrophobic and aromatic ring, features critical for HIV-protease inhibitors. The model exhibits high correlation (R=0.933), less rmsd (1.014), high cross validated correlation coefficient (Q(2)=0.872) among the ten models examined and validated by Fischer's randomization test at 95% confidence level. The acceptable parameters of test set prediction, such as R(pred)(2)=0.768 and r(m(test))(2)=0.711 suggested that external predictivity of the model was significant. The pharmacophore model was used to perform a virtual screening employing the NCI database. Initial hits were sorted using a number of parameters and finally seven compounds were proposed as potential HIV-protease molecules. One potential HIV-protease ligand is reportedly confirmed as an active agent for anti-HIV screening, validating the current approach. It can be postulated that the pharmacophore model facilitates the selection of novel scaffold of HIV-protease inhibitors and can also allow the design of new chemical entities. PMID:25541527

  10. Pharmacophore based approach to design inhibitors in crustaceans: an insight into the molt inhibition response to the receptor guanylyl cyclase.

    PubMed

    Shrivastava, Sajal; Princy, S Adline

    2014-04-01

    The first set of competitive inhibitors of molt inhibiting hormone (MIH) has been developed using the effective approaches such as Hip-Hop, virtual screening and manual alterations. Moreover, the conserved residues at 71 and 72 positions in the molt inhibiting hormone is known to be significant for selective inhibition of ecdysteroidogenesis; thus, the information from mutation and solution structure were used to generate common pharmacophore features. The geometry of the final six-feature pharmacophore was also found to be consistent with the homology-modeled MIH structures from various other decapod crustaceans. The Hypo-1, comprising six features hypothesis was carefully selected as a best pharmacophore model for virtual screening created on the basis of rank score and cluster processes. The hypothesis was validated and the database was virtually screened using this 3D query and the compounds were then manually altered to enhance the fit value. The hits obtained were further filtered for drug-likeness, which is expressed as physicochemical properties that contribute to favorable ADME/Tox profiles to eliminate the molecules exhibit toxicity and poor pharmacokinetics. In conclusion, the higher fit values of CI-1 (4.6), CI-4 (4.9) and CI-7 (4.2) in conjunction with better pharmacokinetic profile made these molecules practically helpful tool to increase production by accelerating molt in crustaceans. The use of feeding sub-therapeutic dosages of these growth enhancers can be very effectively implemented and certainly turn out to be a vital part of emerging nutritional strategies for economically important crustacean livestock. PMID:24772941

  11. Modeling sandhill crane population dynamics

    USGS Publications Warehouse

    Johnson, D.H.

    1979-01-01

    The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

  12. Terminal Model Of Newtonian Dynamics

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1994-01-01

    Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.

  13. Synthesis and Sulfur Electrophilicity of the Nuphar Thiaspirane Pharmacophore

    PubMed Central

    2016-01-01

    We describe a general method to synthesize the iminium tetrahydrothiophene embedded in the dimeric Nuphar alkaloids. In contrast to prior studies, the sulfur atom of the thiaspirane pharmacophore is shown to be electrophilic. This α-thioether reacts with thiophenol or glutathione at ambient temperature to cleave the C–S bond and form a disulfide. Rates of conversion are proportional to the corresponding ammonium ion pKa and exhibit half-lives less than 5 h at a 5 mM concentration of thiol. A simple thiophane analogue of the Nuphar dimers causes apoptosis at single-digit micromolar concentration and labels reactive cysteines at similar levels as the unsaturated iminium “warhead”. Our experiments combined with prior observations suggest the sulfur of the Nuphar dimers can react as an electrophile in cellular environments and that sulfur-triggered retrodimerization can occur in the cell. PMID:27413784

  14. Synthesis and evaluation of transthyretin amyloidosis inhibitors containing carborane pharmacophores

    PubMed Central

    Julius, Richard L.; Farha, Omar K.; Chiang, Janet; Perry, L. Jeanne; Hawthorne, M. Frederick

    2007-01-01

    Carboranes represent a potentially rich but underutilized class of inorganic and catabolism-inert pharmacophores. The regioselectivity and ease of derivatization of carboranes allows for facile syntheses of a wide variety of novel structures. The steric bulk, rigidity, and ease of B- and C-derivatization and lack of π-interactions associated with hydrophobic carboranes may be exploited to enhance the selectivity of previously identified bioactive molecules. Transthyretin (TTR) is a thyroxine-transport protein found in the blood that has been implicated in a variety of amyloid related diseases. Previous investigations have identified a variety of nonsteroidal antiinflammatory drugs (NSAIDs) and structurally related derivatives that imbue kinetic stabilization to TTR, thus inhibiting its dissociative fragmentation and subsequent aggregation to form putative toxic amyloid fibrils. However, the cyclooxygenase (COX) activity associated with these pharmaceuticals may limit their potential as long-term therapeutic agents for TTR amyloid diseases. Here, we report the synthesis and evaluation of carborane-containing analogs of the promising NSAID pharmaceuticals previously identified. The replacement of a phenyl ring in the NSAIDs with a carborane moiety greatly decreases their COX activity with the retention of similar efficacy as an inhibitor of TTR dissociation. The most promising of these compounds, 1-carboxylic acid-7-[3-fluorophenyl]-1,7-dicarba-closo-dodecaborane, showed effectively no COX-1 or COX-2 inhibition at a concentration more than an order of magnitude larger than the concentration at which TTR dissociation is nearly completely inhibited. This specificity is indicative of the potential for the exploitation of the unique properties of carboranes as potent and selective pharmacophores. PMID:17360344

  15. Rational and efficient geometric definition of pharmacophores is essential for the patent process.

    PubMed

    Guérin, Georges-Alexandre; Pratuangdejkul, Jaturong; Alemany, Monica; Launay, Jean-Marie; Manivet, Philippe

    2006-11-01

    The geometric description of pharmacophores suffers from approximations. No consensus has been clearly established, despite the increasing interest in using pharmacophores in drug design and in patent applications. We therefore propose an original definition of a pharmacophore using spherical coordinates. These coordinates give a precise description of each point using three parameters: distance to a geometric origin and two angles. If necessary, these parameters can be easily and rapidly converted to cartesian coordinates. Our method can guarantee, to the patent applicant, the safe protection of his intellectual property by both improving markedly the readability of a pharmacophore definition and bringing, to the person who is skilled in the art, enough information to understand easily the essence of the invention. PMID:17055408

  16. Dynamic Models of Robots with Elastic Hinges

    NASA Astrophysics Data System (ADS)

    Krakhmalev, O. N.

    2016-04-01

    Two dynamic models of robots with elastic hinges are considered. Dynamic models are the implementation of the method based on the Lagrange equation using the transformation matrices of elastic coordinates. Dynamic models make it possible to determine the elastic deviations from programmed motion trajectories caused by elastic deformations in hinges, which are taken into account in directions of change of the corresponding generalized coordinates. One model is the exact implementation of the Lagrange method and makes it possible to determine the total elastic deviation of the robot from the programmed motion trajectory. Another dynamic model is approximated and makes it possible to determine small elastic quasi-static deviations and elastic vibrations. The results of modeling the dynamics by two models are compared to the example of a two-link manipulator system. The considered models can be used when performing investigations of the mathematical accuracy of the robots.

  17. In silico stereo-electronic analysis of PMD (p-Menthane-3-8-Diol) and its derivatives for pharmacophore development may aid discovery of novel insect repellents.

    PubMed

    Bhattacharjee, Apurba K

    2013-09-01

    PMD (p-menthane-3-8-diol) is an insect repellent that can be synthesized chemically or derived from a steam distillate residue of the leaves of lemon eucalyptus, Corymbia citriodora. It is one of the few natural product endorsed by the Center for Disease Control (USA) for topical application to protect against mosquitoes though it is not as effective as the common repellent DEET (N,N -diethyl-1,3-toluamide). However, DEET has several undesirable side effects and toxicity too. Thus, although PMDs are comparatively safer than DEET, no quantitative structure activity relationship (QSAR) and pharmacophore modeling studies have been reported in literature to improve efficacy and aid further development of more effective PMD analogues. In this study, we report results of quantum chemical analysis of stereoelectronic properties and pharmacophore modeling of PMD and eight of its synthetic derivatives to aid discovery and design of more effective PMD analogues. Stereo-electronic analysis indicates that lower aqueous stabilization (favorable lipophilicity) and larger separation of electrostatic potential energy together with a large localized negative electrostatic potential region by the oxygen atom play important roles for repellent activity. Consistent to these properties, the generated pharmacophore model of the PMDs showed two aliphatic hydrophobic and a hydrogen-bond donor features for potent activity. These results aided us to design more effective PMD repellents which are currently under further investigations. PMID:24010930

  18. General Ser/Thr Kinases Pharmacophore Approach for Selective Kinase Inhibitors Search as Exemplified by Design of Potent and Selective Aurora A Inhibitors.

    PubMed

    Vasilevich, Natalya I; Aksenova, Elena A; Kazyulkin, Denis N; Afanasyev, Ilya I

    2016-07-01

    A general pharmachophore model for various types of Ser/Thr kinases was developed. Search for the molecules fitting to this pharmacophore among ASINEX proprietary library revealed a number of compounds, which were tested and appeared to possess some activity against several Ser/Thr kinases such as Aurora A, Aurora B and Haspin. The possibility of performing the fine-tuning of the general Ser/Thr pharmacophore to desired types of kinase to get active and selective inhibitors was exemplified by Aurora A kinase. As a result, several hits in 3-5 nm range of activity against Aurora A kinase with rather good selectivity and ADME properties were obtained. PMID:26825399

  19. 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

  20. Synthesis, activity and pharmacophore development for isatin-β-thiosemicarbazones with selective activity towards multidrug resistant cellsa

    PubMed Central

    Hall, Matthew D.; Salam, Noeris K.; Hellawell, Jennifer L.; Fales, Henry M.; Kensler, Caroline B.; Ludwig, Joseph A.; Szakacs, Gergely; Hibbs, David E.; Gottesman, Michael M.

    2009-01-01

    We have recently identified a new class of compounds that selectively kill cells that express P-glycoprotein (P-gp, MDR1), the ATPase efflux pump that confers multidrug resistance on cancer cells. Several isatin-β-thiosemicarbazones from our initial study have been validated, and a range of analogs synthesized and tested. A number demonstrated improved MDR1-selective activity over the lead, NSC73306 (1). Pharmacophores for cytotoxicity and MDR1-selectivity were generated to delineate the structural features required for activity. The MDR1-selective pharmacophore highlights the importance of aromatic/hydrophobic features at the N4 position of the thiosemicarbazone, and the reliance on the isatin moiety as key bioisosteric contributors. Additionally, a quantitative structure-activity relationship (QSAR) model that yielded a cross-validated correlation coefficient of 0.85 effectively predicts the cytotoxicty of untested thiosemicarbazones. Together, the models serve as effective approaches for predicting structures with MDR1-selective activity, and aid in directing the search for the mechanism of action of 1. PMID:19397322

  1. Screening Ingredients from Herbs against Pregnane X Receptor in the Study of Inductive Herb-Drug Interactions: Combining Pharmacophore and Docking-Based Rank Aggregation

    PubMed Central

    Cui, Zhijie; Kang, Hong; Tang, Kailin; Liu, Qi; Cao, Zhiwei; Zhu, Ruixin

    2015-01-01

    The issue of herb-drug interactions has been widely reported. Herbal ingredients can activate nuclear receptors and further induce the gene expression alteration of drug-metabolizing enzyme and/or transporter. Therefore, the herb-drug interaction will happen when the herbs and drugs are coadministered. This kind of interaction is called inductive herb-drug interactions. Pregnane X Receptor (PXR) and drug-metabolizing target genes are involved in most of inductive herb-drug interactions. To predict this kind of herb-drug interaction, the protocol could be simplified to only screen agonists of PXR from herbs because the relations of drugs with their metabolizing enzymes are well studied. Here, a combinational in silico strategy of pharmacophore modelling and docking-based rank aggregation (DRA) was employed to identify PXR's agonists. Firstly, 305 ingredients were screened out from 820 ingredients as candidate agonists of PXR with our pharmacophore model. Secondly, DRA was used to rerank the result of pharmacophore filtering. To validate our prediction, a curated herb-drug interaction database was built, which recorded 380 herb-drug interactions. Finally, among the top 10 herb ingredients from the ranking list, 6 ingredients were reported to involve in herb-drug interactions. The accuracy of our method is higher than other traditional methods. The strategy could be extended to studies on other inductive herb-drug interactions. PMID:26339628

  2. Modeling population dynamics: A quantile approach.

    PubMed

    Chavas, Jean-Paul

    2015-04-01

    The paper investigates the modeling of population dynamics, both conceptually and empirically. It presents a reduced form representation that provides a flexible characterization of population dynamics. It leads to the specification of a threshold quantile autoregression (TQAR) model, which captures nonlinear dynamics by allowing lag effects to vary across quantiles of the distribution as well as with previous population levels. The usefulness of the model is illustrated in an application to the dynamics of lynx population. We find statistical evidence that the quantile autoregression parameters vary across quantiles (thus rejecting the AR model as well as the TAR model) as well as with past populations (thus rejecting the quantile autoregression QAR model). The results document the nature of dynamics and cycle in the lynx population over time. They show how both the period of the cycle and the speed of population adjustment vary with population level and environmental conditions. PMID:25661501

  3. Multidimensional Langevin Modeling of Nonoverdamped Dynamics

    NASA Astrophysics Data System (ADS)

    Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard

    2015-07-01

    Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.

  4. The Challenges to Coupling Dynamic Geospatial Models

    SciTech Connect

    Goldstein, N

    2006-06-23

    Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.

  5. Pharmacophore-based discovery of FXR-agonists. Part II: Identification of bioactive triterpenes from Ganoderma lucidum

    PubMed Central

    Grienke, Ulrike; Mihály-Bison, Judit; Schuster, Daniela; Afonyushkin, Taras; Binder, Markus; Guan, Shu-hong; Cheng, Chun-ru; Wolber, Gerhard; Stuppner, Hermann; Guo, De-an; Bochkov, Valery N.; Rollinger, Judith M.

    2011-01-01

    The farnesoid X receptor (FXR) belonging to the metabolic subfamily of nuclear receptors is a ligand-induced transcriptional activator. Its central function is the physiological maintenance of bile acid homeostasis including the regulation of glucose and lipid metabolism. Accessible structural information about its ligand-binding domain renders FXR an attractive target for in silico approaches. Integrated to natural product research these computational tools assist to find novel bioactive compounds showing beneficial effects in prevention and treatment of, for example, the metabolic syndrome, dyslipidemia, atherosclerosis, and type 2 diabetes. Virtual screening experiments of our in-house Chinese Herbal Medicine database with structure-based pharmacophore models, previously generated and validated, revealed mainly lanostane-type triterpenes of the TCM fungus Ganoderma lucidum Karst. as putative FXR ligands. To verify the prediction of the in silico approach, two Ganoderma fruit body extracts and compounds isolated thereof were pharmacologically investigated. Pronounced FXR-inducing effects were observed for the extracts at a concentration of 100 μg/mL. Intriguingly, five lanostanes out of 25 secondary metabolites from G. lucidum, that is, ergosterol peroxide (2), lucidumol A (11), ganoderic acid TR (12), ganodermanontriol (13), and ganoderiol F (14), dose-dependently induced FXR in the low micromolar range in a reporter gene assay. To rationalize the binding interactions, additional pharmacophore profiling and molecular docking studies were performed, which allowed establishing a first structure–activity relationship of the investigated triterpenes. PMID:22014750

  6. Hydration dynamics near a model protein surface

    SciTech Connect

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-09-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces.

  7. Benchmarking of Planning Models Using Recorded Dynamics

    SciTech Connect

    Huang, Zhenyu; Yang, Bo; Kosterev, Dmitry

    2009-03-15

    Power system planning extensively uses model simulation to understand the dynamic behaviors and determine the operating limits of a power system. Model quality is key to the safety and reliability of electricity delivery. Planning model benchmarking, or model validation, has been one of the central topics in power engineering studies for years. As model validation aims at obtaining reasonable models to represent dynamic behavior of power system components, it has been essential to validate models against actual measurements. The development of phasor technology provides such measurements and represents a new opportunity for model validation as phasor measurements can capture power system dynamics with high-speed, time-synchronized data. Previously, methods for rigorous comparison of model simulation and recorded dynamics have been developed and applied to quantify model quality of power plants in the Western Electricity Coordinating Council (WECC). These methods can locate model components which need improvement. Recent work continues this effort and focuses on how model parameters may be calibrated to match recorded dynamics after the problematic model components are identified. A calibration method using Extended Kalman Filter technique is being developed. This paper provides an overview of prior work on model validation and presents new development on the calibration method and initial results of model parameter calibration.

  8. Map-based models in neuronal dynamics

    NASA Astrophysics Data System (ADS)

    Ibarz, B.; Casado, J. M.; Sanjuán, M. A. F.

    2011-04-01

    Ever since the pioneering work of Hodgkin and Huxley, biological neuron models have consisted of ODEs representing the evolution of the transmembrane voltage and the dynamics of ionic conductances. It is only recently that discrete dynamical systems-also known as maps-have begun to receive attention as valid phenomenological neuron models. The present review tries to provide a coherent perspective of map-based biological neuron models, describing their dynamical properties; stressing the similarities and differences, both among them and in relation to continuous-time models; exploring their behavior in networks; and examining their wide-ranging possibilities of application in computational neuroscience.

  9. [Review of dynamic global vegetation models (DGVMs)].

    PubMed

    Che, Ming-Liang; Chen, Bao-Zhang; Wang, Ying; Guo, Xiang-Yun

    2014-01-01

    Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology. Then the future research directions of DGVMs were pointed out, i. e. improving the PFT scheme, refining the vegetation dynamic mechanism, and implementing a model inter-comparison project. PMID:24765870

  10. Chaotic dynamics in a simple dynamical green ocean plankton model

    NASA Astrophysics Data System (ADS)

    Cropp, Roger; Moroz, Irene M.; Norbury, John

    2014-11-01

    The exchange of important greenhouse gases between the ocean and atmosphere is influenced by the dynamics of near-surface plankton ecosystems. Marine plankton ecosystems are modified by climate change creating a feedback mechanism that could have significant implications for predicting future climates. The collapse or extinction of a plankton population may push the climate system across a tipping point. Dynamic green ocean models (DGOMs) are currently being developed for inclusion into climate models to predict the future state of the climate. The appropriate complexity of the DGOMs used to represent plankton processes is an ongoing issue, with models tending to become more complex, with more complicated dynamics, and an increasing propensity for chaos. We consider a relatively simple (four-population) DGOM of phytoplankton, zooplankton, bacteria and zooflagellates where the interacting plankton populations are connected by a single limiting nutrient. Chaotic solutions are possible in this 4-dimensional model for plankton population dynamics, as well as in a reduced 3-dimensional model, as we vary two of the key mortality parameters. Our results show that chaos is robust to the variation of parameters as well as to the presence of environmental noise, where the attractor of the more complex system is more robust than the attractor of its simplified equivalent. We find robust chaotic dynamics in low trophic order ecological models, suggesting that chaotic dynamics might be ubiquitous in the more complex models, but this is rarely observed in DGOM simulations. The physical equations of DGOMs are well understood and are constrained by conservation principles, but the ecological equations are not well understood, and generally have no explicitly conserved quantities. This work, in the context of the paucity of the empirical and theoretical bases upon which DGOMs are constructed, raises the interesting question of whether DGOMs better represent reality if they include

  11. Very Large System Dynamics Models - Lessons Learned

    SciTech Connect

    Jacob J. Jacobson; Leonard Malczynski

    2008-10-01

    This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.

  12. Comparing models of Red Knot population dynamics

    USGS Publications Warehouse

    McGowan, Conor

    2015-01-01

    Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

  13. Human systems dynamics: Toward a computational model

    NASA Astrophysics Data System (ADS)

    Eoyang, Glenda H.

    2012-09-01

    A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

  14. FRF based joint dynamics modeling and identification

    NASA Astrophysics Data System (ADS)

    Mehrpouya, Majid; Graham, Eldon; Park, Simon S.

    2013-08-01

    Complex structures, such as machine tools, are comprised of several substructures connected to each other through joints to form the assembled structures. Joints can have significant contributions on the behavior of the overall assembly and ignoring joint effects in the design stage may result in considerable deviations from the actual dynamic behavior. The identification of joint dynamics enables us to accurately predict overall assembled dynamics by mathematically combining substructure dynamics through the equilibrium and compatibility conditions at the joint. The essence of joint identification is the determination of the difference between the measured overall dynamics and the rigidly coupled substructure dynamics. In this study, we investigate the inverse receptance coupling (IRC) method and the point-mass joint model, which considers the joint as lumped mass, damping and stiffness elements. The dynamic properties of the joint are investigated using both methods through a finite element (FE) simulation and experimental tests. `100

  15. Modeling microbial growth and dynamics.

    PubMed

    Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M

    2015-11-01

    Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers. PMID:26298697

  16. Differential equation models for sharp threshold dynamics.

    PubMed

    Schramm, Harrison C; Dimitrov, Nedialko B

    2014-01-01

    We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. PMID:24184349

  17. Equivalent dynamic model of DEMES rotary joint

    NASA Astrophysics Data System (ADS)

    Zhao, Jianwen; Wang, Shu; Xing, Zhiguang; McCoul, David; Niu, Junyang; Huang, Bo; Liu, Liwu; Leng, Jinsong

    2016-07-01

    The dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by a small voltage-induced strain of the dielectric elastomer (DE), so it is a suitable candidate to make a rotary joint for a soft robot. Dynamic analysis is necessary for some applications, but the dynamic response of DEMESs is difficult to model because of the complicated morphology and viscoelasticity of the DE film. In this paper, a method composed of theoretical analysis and experimental measurement is presented to model the dynamic response of a DEMES rotary joint under an alternating voltage. Based on measurements of equivalent driving force and damping of the DEMES, the model can be derived. Some experiments were carried out to validate the equivalent dynamic model. The maximum angle error between model and experiment is greater than ten degrees, but it is acceptable to predict angular velocity of the DEMES, therefore, it can be applied in feedforward–feedback compound control.

  18. Modeling dynamical geometry with lattice gas automata

    SciTech Connect

    Hasslacher, B.; Meyer, D.A.

    1998-06-27

    Conventional lattice gas automata consist of particles moving discretely on a fixed lattice. While such models have been quite successful for a variety of fluid flow problems, there are other systems, e.g., flow in a flexible membrane or chemical self-assembly, in which the geometry is dynamical and coupled to the particle flow. Systems of this type seem to call for lattice gas models with dynamical geometry. The authors construct such a model on one dimensional (periodic) lattices and describe some simulations illustrating its nonequilibrium dynamics.

  19. Dynamics Modelling of Biolistic Gene Guns

    SciTech Connect

    Zhang, M.; Tao, W.; Pianetta, P.A.

    2009-06-04

    The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model for improving and manipulating performance of the biolistic gene gun.

  20. Hematin Polymerization Assay as a High-Throughput Screen for Identification of New Antimalarial Pharmacophores

    PubMed Central

    Kurosawa, Yae; Dorn, Arnulf; Kitsuji-Shirane, Michiko; Shimada, Hisao; Satoh, Tomoko; Matile, Hugues; Hofheinz, Werner; Masciadri, Raffaello; Kansy, Manfred; Ridley, Robert G.

    2000-01-01

    Hematin polymerization is a parasite-specific process that enables the detoxification of heme following its release in the lysosomal digestive vacuole during hemoglobin degradation, and represents both an essential and a unique pharmacological drug target. We have developed a high-throughput in vitro microassay of hematin polymerization based on the detection of 14C-labeled hematin incorporated into polymeric hemozoin (malaria pigment). The assay uses 96-well filtration microplates and requires 12 h and a Wallac 1450 MicroBeta liquid scintillation counter. The robustness of the assay allowed the rapid screening and evaluation of more than 100,000 compounds. Random screening was complemented by the development of a pharmacophore hypothesis using the “Catalyst” program and a large amount of data available on the inhibitory activity of a large library of 4-aminoquinolines. Using these methods, we identified “hit” compounds belonging to several chemical structural classes that had potential antimalarial activity. Follow-up evaluation of the antimalarial activity of these compounds in culture and in the Plasmodium berghei murine model further identified compounds with actual antimalarial activity. Of particular interest was a triarylcarbinol (Ro 06-9075) and a related benzophenone (Ro 22-8014) that showed oral activity in the murine model. These compounds are chemically accessible and could form the basis of a new antimalarial medicinal chemistry program. PMID:10991837

  1. Hematin polymerization assay as a high-throughput screen for identification of new antimalarial pharmacophores.

    PubMed

    Kurosawa, Y; Dorn, A; Kitsuji-Shirane, M; Shimada, H; Satoh, T; Matile, H; Hofheinz, W; Masciadri, R; Kansy, M; Ridley, R G

    2000-10-01

    Hematin polymerization is a parasite-specific process that enables the detoxification of heme following its release in the lysosomal digestive vacuole during hemoglobin degradation, and represents both an essential and a unique pharmacological drug target. We have developed a high-throughput in vitro microassay of hematin polymerization based on the detection of (14)C-labeled hematin incorporated into polymeric hemozoin (malaria pigment). The assay uses 96-well filtration microplates and requires 12 h and a Wallac 1450 MicroBeta liquid scintillation counter. The robustness of the assay allowed the rapid screening and evaluation of more than 100, 000 compounds. Random screening was complemented by the development of a pharmacophore hypothesis using the "Catalyst" program and a large amount of data available on the inhibitory activity of a large library of 4-aminoquinolines. Using these methods, we identified "hit" compounds belonging to several chemical structural classes that had potential antimalarial activity. Follow-up evaluation of the antimalarial activity of these compounds in culture and in the Plasmodium berghei murine model further identified compounds with actual antimalarial activity. Of particular interest was a triarylcarbinol (Ro 06-9075) and a related benzophenone (Ro 22-8014) that showed oral activity in the murine model. These compounds are chemically accessible and could form the basis of a new antimalarial medicinal chemistry program. PMID:10991837

  2. Development of CNS multi-receptor ligands: Modification of known D2 pharmacophores.

    PubMed

    Etukala, Jagan R; Zhu, Xue Y; Eyunni, Suresh V K; Onyameh, Edem K; Ofori, Edward; Bricker, Barbara A; Kang, Hye J; Huang, Xi-Ping; Roth, Bryan L; Ablordeppey, Seth Y

    2016-08-15

    Several known D2 pharmacophores have been explored as templates for identifying ligands with multiple binding affinities at dopamine and serotonin receptors considered as clinically relevant receptors in the treatment of neuropsychiatric diseases. This approach has resulted in the identification of ligands that target multiple CNS receptors while avoiding others associated with deleterious effects. In particular, compounds 11, 15 and 22 may have potential for further development as antipsychotic agents as they favorably interact with the clinically relevant receptors including D2R, 5-HT1AR, and 5-HT7R. We have also identified the pair of compounds 11 and 10 as high affinity D2R ligands with and without SERT binding affinities, respectively. These differential binding profiles endow the pair with the potential for evaluating SERT contributions to antipsychotic drug activity in animal behavioral models. In addition, compound 11 has no significant affinity for 5-HT2CR and binds only moderately to the H1R, suggesting it may not induce weight gain or sedation when used clinically. Taken together, compound 11 displays an interesting pharmacological profile that necessitates the evaluation of its functional and in vivo effects in animal models which are currently ongoing. PMID:27364609

  3. Markov state models of biomolecular conformational dynamics

    PubMed Central

    Chodera, John D.; Noé, Frank

    2014-01-01

    It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges. PMID:24836551

  4. Dynamic coupling of three hydrodynamic models

    NASA Astrophysics Data System (ADS)

    Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

    2008-12-01

    The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The

  5. A Microcomputer Dynamical Modelling System.

    ERIC Educational Resources Information Center

    Ogborn, Jon; Wong, Denis

    1984-01-01

    Presents a system that permits students to engage directly in the process of modelling and to learn some important lessons about models and classes of models. The system described currently runs on RML 380Z and 480Z, Apple II and IIe, and BBC model B microcomputers. (JN)

  6. First Pharmacophore-Based Identification of Androgen Receptor Down-regulating Agents: Discovery of Potent Anti-Prostate Cancer Agents

    PubMed Central

    Purushottamachar, Puranik; Khandelwal, Aakanksha; Chopra, Pankaj; Maheshwari, Neha; Gediya, Lalji K; Vasaitis, Tadas S.; Bruno, Robert; Clement, Omoshile O.; Njar, Vincent C. O.

    2007-01-01

    A qualitative 3D pharmacophore model (a common feature based model or Catalyst HipHop algorithm) was developed for well known natural product androgen receptor down-regulating agents (ARDAs). The four common chemical features identified included: one hydrophobic group, one ring aromatic group and two hydrogen bond acceptors. This model served as a template in virtual screening of the Maybridge and NCI databases that resulted in identification of 6 new ARDAs (EC50 values 17.5 – 212 μM). Five of these molecules strongly inhibited the growth of human prostate LNCaP cells. These novel compounds may be used as leads to develop other novel anti-prostate cancer agents. PMID:17383188

  7. First pharmacophore-based identification of androgen receptor down-regulating agents: discovery of potent anti-prostate cancer agents.

    PubMed

    Purushottamachar, Puranik; Khandelwal, Aakanksha; Chopra, Pankaj; Maheshwari, Neha; Gediya, Lalji K; Vasaitis, Tadas S; Bruno, Robert D; Clement, Omoshile O; Njar, Vincent C O

    2007-05-15

    A qualitative 3D pharmacophore model (a common feature based model or Catalyst HipHop algorithm) was developed for well-known natural product androgen receptor down-regulating agents (ARDAs). The four common chemical features identified included: one hydrophobic group, one ring aromatic group, and two hydrogen bond acceptors. This model served as a template in virtual screening of the Maybridge and NCI databases that resulted in identification of six new ARDAs (EC(50) values 17.5-212 microM). Five of these molecules strongly inhibited the growth of human prostate LNCaP cells. These novel compounds may be used as leads to develop other novel anti-prostate cancer agents. PMID:17383188

  8. Identification of the Benzyloxyphenyl Pharmacophore: A Structural Unit That Promotes Sodium Channel Slow Inactivation

    PubMed Central

    2012-01-01

    Four compounds that contained the N-benzyl 2-amino-3-methoxypropionamide unit were evaluated for their ability to modulate Na+ currents in catecholamine A differentiated CAD neuronal cells. The compounds differed by the absence or presence of either a terminal N-acetyl group or a (3-fluoro)benzyloxy moiety positioned at the 4′-benzylamide site. Analysis of whole-cell patch-clamp electrophysiology data showed that the incorporation of the (3-fluoro)benzyloxy unit, to give the (3-fluoro)benzyloxyphenyl pharmacophore, dramatically enhanced the magnitude of Na+ channel slow inactivation. In addition, N-acetylation markedly increased the stereoselectivity for Na+ channel slow inactivation. Furthermore, we observed that Na+ channel frequency (use)-dependent block was maintained upon inclusion of this pharmacophore. Confirmation of the importance of the (3-fluoro)benzyloxyphenyl pharmacophore was shown by examining compounds where the N-benzyl 2-amino-3-methoxypropionamide unit was replaced by a N-benzyl 2-amino-3-methylpropionamide moiety, as well as examining a series of compounds that did not contain an amino acid group but retained the pharmacophore unit. Collectively, the data indicated that the (3-fluoro)benzyloxyphenyl unit is a novel pharmacophore for the modulation of Na+ currents. PMID:23259039

  9. Dynamic modeling of emulsion polymerization reactors

    SciTech Connect

    Penlidis, A.; Hamielec, A.E.; MacGregor, J.F.

    1985-06-01

    This paper is a survey of recent published works on the dynamic and steady state modeling of emulsion homo- and copolymerization in batch, semicontinuous , and continuous latex reactors. Contributions to our understanding of diffusion-controlled termination and propagation reactions, molecular weight, long chain branching and crosslinking development, polymer particle nucleation, and of the dynamics of continuous emulsion polymerization are critically reviewed.

  10. Flexible aircraft dynamic modeling for dynamic analysis and control synthesis

    NASA Technical Reports Server (NTRS)

    Schmidt, David K.

    1989-01-01

    The linearization and simplification of a nonlinear, literal model for flexible aircraft is highlighted. Areas of model fidelity that are critical if the model is to be used for control system synthesis are developed and several simplification techniques that can deliver the necessary model fidelity are discussed. These techniques include both numerical and analytical approaches. An analytical approach, based on first-order sensitivity theory is shown to lead not only to excellent numerical results, but also to closed-form analytical expressions for key system dynamic properties such as the pole/zero factors of the vehicle transfer-function matrix. The analytical results are expressed in terms of vehicle mass properties, vibrational characteristics, and rigid-body and aeroelastic stability derivatives, thus leading to the underlying causes for critical dynamic characteristics.

  11. Automated adaptive inference of phenomenological dynamical models

    PubMed Central

    Daniels, Bryan C.; Nemenman, Ilya

    2015-01-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

  12. Constructing minimal models for complex system dynamics

    NASA Astrophysics Data System (ADS)

    Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László

    2015-05-01

    One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.

  13. Automated adaptive inference of phenomenological dynamical models

    NASA Astrophysics Data System (ADS)

    Daniels, Bryan C.; Nemenman, Ilya

    2015-08-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

  14. Dynamic metabolic models in context: biomass backtracking.

    PubMed

    Tummler, Katja; Kühn, Clemens; Klipp, Edda

    2015-08-01

    Mathematical modeling has proven to be a powerful tool to understand and predict functional and regulatory properties of metabolic processes. High accuracy dynamic modeling of individual pathways is thereby opposed by simplified but genome scale constraint based approaches. A method that links these two powerful techniques would greatly enhance predictive power but is so far lacking. We present biomass backtracking, a workflow that integrates the cellular context in existing dynamic metabolic models via stoichiometrically exact drain reactions based on a genome scale metabolic model. With comprehensive examples, for different species and environmental contexts, we show the importance and scope of applications and highlight the improvement compared to common boundary formulations in existing metabolic models. Our method allows for the contextualization of dynamic metabolic models based on all available information. We anticipate this to greatly increase their accuracy and predictive power for basic research and also for drug development and industrial applications. PMID:26189715

  15. Identification of novel EZH2 inhibitors through pharmacophore-based virtual screening and biological assays.

    PubMed

    Wu, Yunlong; Hu, Junchi; Ding, Hong; Chen, Limin; Zhang, Yuanyuan; Liu, Rongfeng; Xu, Pan; Du, Daohai; Lu, Wenchao; Liu, Jingqiu; Liu, Yan; Liu, Yu-Chih; Lu, Junyan; Zhang, Jin; Yao, Zhiyi; Luo, Cheng

    2016-08-01

    Polycomb repressive complex 2 (PRC2) acts as a primary writer for di- and tri-methylation of histone H3 at lysine 27. This protein plays an essential role in silencing gene expression. Enhancer of zeste 2 (EZH2), the catalytic subunit of PRC2, is considered as a promising therapeutic target for cancer. GSK126, a specific inhibitor of EZH2, is undergoing phase I trials for hypermethylation-related cancers. In addition, many derivatives of GSK126 are also commonly used in laboratory investigations. However, studies on the mechanism and drug development of EZH2 are limited by the absence of structural diversity of these inhibitors because they share similar SAM-like scaffolds. In this study, we generated a pharmacophore model based on reported EZH2 inhibitors and performed in silico screenings. Experimental validations led to the identification of two novel EZH2 inhibitors, DCE_42 and DCE_254, with IC50 values of 23 and 11μM, respectively. They also displayed significant anti-proliferation activity against lymphoma cell lines. Thus, we discovered potent EZH2 inhibitors with novel scaffold using combined in silico screening and experimental study. Results from this study can also guide further development of novel specific EZH2 inhibitors. PMID:27289323

  16. Single timepoint models of dynamic systems.

    PubMed

    Sachs, K; Itani, S; Fitzgerald, J; Schoeberl, B; Nolan, G P; Tomlin, C J

    2013-08-01

    Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We encounter an unexpected problem not previously described in elucidating connectivity structure from dynamic systems, show how this confounds structure learning of the system and discuss possible approaches to overcome the confounding effect. Finally, we test our hypotheses on an accurate dynamic model of the IGF signalling pathway. We use two structure-learning methods at four time points to contrast the performance and robustness of those methods in terms of recovering correct connectivity. PMID:24511382

  17. Single timepoint models of dynamic systems

    PubMed Central

    Sachs, K.; Itani, S.; Fitzgerald, J.; Schoeberl, B.; Nolan, G. P.; Tomlin, C. J.

    2013-01-01

    Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We encounter an unexpected problem not previously described in elucidating connectivity structure from dynamic systems, show how this confounds structure learning of the system and discuss possible approaches to overcome the confounding effect. Finally, we test our hypotheses on an accurate dynamic model of the IGF signalling pathway. We use two structure-learning methods at four time points to contrast the performance and robustness of those methods in terms of recovering correct connectivity. PMID:24511382

  18. Dynamics of two nonlinear oligopoly models

    NASA Astrophysics Data System (ADS)

    Ibrahim, Adyda

    2014-06-01

    This paper considers an n firms oligopoly model with isoelastic demand function and linear cost function. This model is introduced in two different dynamical systems. In the first system, firms are assumed have naive expectation, while in the second system, firms are assumed to have bounded rationality. We study the dynamics of both dynamical systems in the special case of firms behaving identically. The main result shows that as the number of firm increases, the equilibrium in the first system becomes unstable when the number of firms is greater than four, while in the second system, there is a change in the region of stability for the equilibrium.

  19. Swarm Intelligence for Urban Dynamics Modelling

    NASA Astrophysics Data System (ADS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  20. Swarm Intelligence for Urban Dynamics Modelling

    SciTech Connect

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-04-16

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  1. Novel sulfonanilide analogs decrease aromatase activity in breast cancer cells: synthesis, biological evaluation, and ligand-based pharmacophore identification.

    PubMed

    Su, Bin; Tian, Ran; Darby, Michael V; Brueggemeier, Robert W

    2008-03-13

    Aromatase converts androgens to estrogens and is a particularly attractive target in the treatment of estrogen receptor positive breast cancer. Previously, the COX-2 selective inhibitor nimesulide and analogs decreased aromatase expression and enzyme activity independent of COX-2 inhibition. In this manuscript, a combinatorial approach was used to generate diversely substituted novel sulfonanilides by parallel synthesis. Their pharmacological evaluation as agents for suppression of aromatase activity in SK-BR-3 breast cancer cells was extensively explored. A ligand-based pharmacophore model was elaborated for selective aromatase modulation (SAM) using the Catalyst HipHop algorithms. The best qualitative model consisted of four features: one aromatic ring, two hydrogen bond acceptors, and one hydrophobic function. Several lead compounds have also been tested in aromatase transfected MCF-7 cells, and they significantly suppressed cellular aromatase activity. The results suggest that both genomic and nongenomic mechanisms of these compounds are involved within the aromatase suppression effect. PMID:18271519

  2. Battery electrochemical nonlinear/dynamic SPICE model

    SciTech Connect

    Glass, M.C.

    1996-12-31

    An Integrated Battery Model has been produced which accurately represents DC nonlinear battery behavior together with transient dynamics. The NiH{sub 2} battery model begins with a given continuous-function electrochemical math model. The math model for the battery consists of the sum of two electrochemical process DC currents, which are a function of the battery terminal voltage. This paper describes procedures for realizing a voltage-source SPICE model which implements the electrochemical equations using behavioral sources. The model merges the essentially DC non-linear behavior of the electrochemical model, together with the empirical AC dynamic terminal impedance from measured data. Thus the model integrates the short-term linear impedance behavior, with the long-term nonlinear DC resistance behavior. The long-duration non-Faradaic capacitive behavior of the battery is represented by a time constant. Outputs of the model include battery voltage/current, state-of-charge, and charge-current efficiency.

  3. 3D Pharmacophore, hierarchical methods, and 5-HT4 receptor binding data.

    PubMed

    Varin, Thibault; Saettel, Nicolas; Villain, Jonathan; Lesnard, Aurelien; Dauphin, François; Bureau, Ronan; Rault, Sylvain

    2008-10-01

    5-Hydroxytryptamine subtype-4 (5-HT(4)) receptors have stimulated considerable interest amongst scientists and clinicians owing to their importance in neurophysiology and potential as therapeutic targets. A comparative analysis of hierarchical methods applied to data from one thousand 5-HT(4) receptor-ligand binding interactions was carried out. The chemical structures were described as chemical and pharmacophore fingerprints. The definitions of indices, related to the quality of the hierarchies in being able to distinguish between active and inactive compounds, revealed two interesting hierarchies with the Unity (1 active cluster) and pharmacophore fingerprints (4 active clusters). The results of this study also showed the importance of correct choice of metrics as well as the effectiveness of a new alternative of the Ward clustering algorithm named Energy (Minimum E-Distance method). In parallel, the relationship between these classifications and a previously defined 3D 5-HT(4) antagonist pharmacophore was established. PMID:18821249

  4. Integration of Dynamic Models in Range Operations

    NASA Technical Reports Server (NTRS)

    Bardina, Jorge; Thirumalainambi, Rajkumar

    2004-01-01

    This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

  5. Dynamics of the Standard Model

    NASA Astrophysics Data System (ADS)

    Donoghue, John F.; Golowich, Eugene; Holstein, Barry R.

    2014-04-01

    Preface; 1. Inputs to the Standard Model; 2. Interactions of the Standard Model; 3. Symmetries and anomalies; 4. Introduction to effective field theory; 5. Charged leptons; 6. Neutrinos; 7. Effective field theory for low energy QCD; 8. Weak interactions of Kaons; 9. Mass mixing and CP violation; 10. The Nc-1 expansion; 11. Phenomenological models; 12. Baryon properties; 13. Hadron spectroscopy; 14. Weak interactions of heavy quarks; 15. The Higgs boson; 16. The electroweak sector; Appendixes; References; Index.

  6. Dynamical model for DNA sequences

    NASA Astrophysics Data System (ADS)

    Allegrini, P.; Barbi, M.; Grigolini, P.; West, B. J.

    1995-11-01

    We address the problem of DNA sequences, developing a ``dynamical'' method based on the assumption that the statistical properties of DNA paths are determined by the joint action of two processes, one deterministic with long-range correlations, and the other random and δ-function correlated. The generator of the deterministic evolution is a nonlinear map, belonging to a class of maps recently tailored to mimic the processes of weak chaos that are responsible for the birth of anomalous diffusion. It is assumed that the deterministic process corresponds to unknown biological rules that determine the DNA path, whereas the noise mimics the influence of an infinite-dimensional environment on the biological process under study. We prove that the resulting diffusion process, if the effect of the random process is neglected, is an α-stable Lévy process with 1<α<2. We also show that, if the diffusion process is determined by the joint action of the deterministic and the random process, the correlation effects of the ``deterministic dynamics'' are cancelled on the short-range scale, but show up in the long-range one. We denote our prescription to generate statistical sequences as the copying mistake map (CMM). We carry out our analysis of several DNA sequences and their CMM realizations with a variety of techniques, and we especially focus on a method of regression to equilibrium, which we call the Onsager analysis. With these techniques we establish the statistical equivalence of the real DNA sequences with their CMM realizations. We show that long-range correlations are present in exons as well as in introns, but are difficult to detect, since the exon ``dynamics'' is shown to be determined by the entanglement of three distinct and independent CMM's.

  7. Multi-scale modelling and dynamics

    NASA Astrophysics Data System (ADS)

    Müller-Plathe, Florian

    Moving from a fine-grained particle model to one of lower resolution leads, with few exceptions, to an acceleration of molecular mobility, higher diffusion coefficient, lower viscosities and more. On top of that, the level of acceleration is often different for different dynamical processes as well as for different state points. While the reasons are often understood, the fact that coarse-graining almost necessarily introduces unpredictable acceleration of the molecular dynamics severely limits its usefulness as a predictive tool. There are several attempts under way to remedy these shortcoming of coarse-grained models. On the one hand, we follow bottom-up approaches. They attempt already when the coarse-graining scheme is conceived to estimate their impact on the dynamics. This is done by excess-entropy scaling. On the other hand, we also pursue a top-down development. Here we start with a very coarse-grained model (dissipative particle dynamics) which in its native form produces qualitatively wrong polymer dynamics, as its molecules cannot entangle. This model is modified by additional temporary bonds, so-called slip springs, to repair this defect. As a result, polymer melts and solutions described by the slip-spring DPD model show correct dynamical behaviour. Read more: ``Excess entropy scaling for the segmental and global dynamics of polyethylene melts'', E. Voyiatzis, F. Müller-Plathe, and M.C. Böhm, Phys. Chem. Chem. Phys. 16, 24301-24311 (2014). [DOI: 10.1039/C4CP03559C] ``Recovering the Reptation Dynamics of Polymer Melts in Dissipative Particle Dynamics Simulations via Slip-Springs'', M. Langeloth, Y. Masubuchi, M. C. Böhm, and F. Müller-Plathe, J. Chem. Phys. 138, 104907 (2013). [DOI: 10.1063/1.4794156].

  8. Uncertainty and Sensitivity in Surface Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    Kettner, Albert J.; Syvitski, James P. M.

    2016-05-01

    Papers for this special issue on 'Uncertainty and Sensitivity in Surface Dynamics Modeling' heralds from papers submitted after the 2014 annual meeting of the Community Surface Dynamics Modeling System or CSDMS. CSDMS facilitates a diverse community of experts (now in 68 countries) that collectively investigate the Earth's surface-the dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere, by promoting, developing, supporting and disseminating integrated open source software modules. By organizing more than 1500 researchers, CSDMS has the privilege of identifying community strengths and weaknesses in the practice of software development. We recognize, for example, that progress has been slow on identifying and quantifying uncertainty and sensitivity in numerical modeling of earth's surface dynamics. This special issue is meant to raise awareness for these important subjects and highlight state-of-the-art progress.

  9. Energy Balance Models and Planetary Dynamics

    NASA Technical Reports Server (NTRS)

    Domagal-Goldman, Shawn

    2012-01-01

    We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

  10. Dynamic and Structural Gas Turbine Engine Modeling

    NASA Technical Reports Server (NTRS)

    Turso, James A.

    2003-01-01

    Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.

  11. Stirling Engine Dynamic System Modeling

    NASA Technical Reports Server (NTRS)

    Nakis, Christopher G.

    2004-01-01

    The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

  12. Haptics-based dynamic implicit solid modeling.

    PubMed

    Hua, Jing; Qin, Hong

    2004-01-01

    This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback. PMID:15794139

  13. Synaptic dynamics: linear model and adaptation algorithm.

    PubMed

    Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W

    2014-08-01

    In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and

  14. Modeling of Intracranial Pressure Dynamics

    PubMed Central

    Griffith, Richard L.; Sullivan, Humbert G.; Miller, J. Douglas

    1978-01-01

    Digital computer simulation is utilized to test hypotheses regarding poorly understood mechanisms of intracranial pressure change. The simulation produces graphic output similar to records from polygraph recorders used in patient monitoring and in animal experimentation. The structure of the model is discussed. The mathematic model perfected by the comparison between simulation and experiment will constitute a formulation of medical information applicable to automated clinical monitoring and treatment of intracranial hypertension.

  15. Modeling Dynamic Regulatory Processes in Stroke.

    SciTech Connect

    McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.; Lancaster, Mary J.; Shankaran, Harish; Vartanian, Keri B.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2012-10-11

    The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to develop dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.

  16. Combination of pharmacophore hypothesis and molecular docking to identify novel inhibitors of HCV NS5B polymerase.

    PubMed

    Harikishore, Amaravadhi; Li, Enlin; Lee, Jia Jun; Cho, Nam-Joon; Yoon, Ho Sup

    2015-08-01

    Hepatitis C virus (HCV) infection or HCV-related liver diseases are now shown to cause more than 350,000 deaths every year. Adaptability of HCV genome to vary its composition and the existence of multiple strains makes it more difficult to combat the emergence of drug-resistant HCV infections. Among the HCV polyprotein which has both the structural and non-structural regions, the non-structural protein NS5B RNA-dependent RNA polymerase (RdRP) mainly mediates the catalytic role of RNA replication in conjunction with its viral protein machinery as well as host chaperone proteins. Lack of such RNA-dependent RNA polymerase enzyme in host had made it an attractive and hotly pursued target for drug discovery efforts. Recent drug discovery efforts targeting HCV RdRP have seen success with FDA approval for sofosbuvir as a direct-acting antiviral against HCV infection. However, variations in drug-binding sites induce drug resistance, and therefore targeting allosteric sites could delay the emergence of drug resistance. In this study, we focussed on allosteric thumb site II of the non-structural protein NS5B RNA-dependent RNA polymerase and developed a five-feature pharmacophore hypothesis/model which estimated the experimental activity with a strong correlation of 0.971 & 0.944 for training and test sets, respectively. Further, the Güner-Henry score of 0.6 suggests that the model was able to discern the active and inactive compounds and enrich the true positives during a database search. In this study, database search and molecular docking results supported by experimental HCV viral replication inhibition assays suggested ligands with best fitness to the pharmacophore model dock to the key residues involved in thumbs site II, which inhibited the HCV 1b viral replication in sub-micro-molar range. PMID:25862642

  17. Dynamics of internal models in game players

    NASA Astrophysics Data System (ADS)

    Taiji, Makoto; Ikegami, Takashi

    1999-10-01

    A new approach for the study of social games and communications is proposed. Games are simulated between cognitive players who build the opponent’s internal model and decide their next strategy from predictions based on the model. In this paper, internal models are constructed by the recurrent neural network (RNN), and the iterated prisoner’s dilemma game is performed. The RNN allows us to express the internal model in a geometrical shape. The complicated transients of actions are observed before the stable mutually defecting equilibrium is reached. During the transients, the model shape also becomes complicated and often experiences chaotic changes. These new chaotic dynamics of internal models reflect the dynamical and high-dimensional rugged landscape of the internal model space.

  18. A stochastic evolutionary model for survival dynamics

    NASA Astrophysics Data System (ADS)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2014-09-01

    The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in different contexts. Here we propose a generative model to capture the essential dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. In our model, the only implicit assumption made is that the longer an actor has been in the system, the more likely it is to have failed. We derive a power-law distribution for the process and provide preliminary empirical evidence for the validity of the model from two well-known survival analysis data sets.

  19. Dynamical modeling of laser ablation processes

    SciTech Connect

    Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.

    1995-09-01

    Several physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume; plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms; gas dynamic, hydrodynamic, and collisional descriptions of plume transport; and molecular dynamics models of the interaction of plume particles with the deposition substrate. The complexity of the phenomena involved in the laser ablation process is matched by the diversity of the modeling task, which combines materials science, atomic physics, and plasma physics.

  20. Dynamics Simulation Model for Space Tethers

    NASA Technical Reports Server (NTRS)

    Levin, E. M.; Pearson, J.; Oldson, J. C.

    2006-01-01

    This document describes the development of an accurate model for the dynamics of the Momentum Exchange Electrodynamic Reboost (MXER) system. The MXER is a rotating tether about 100-km long in elliptical Earth orbit designed to catch payloads in low Earth orbit and throw them to geosynchronous orbit or to Earth escape. To ensure successful rendezvous between the MXER tip catcher and a payload, a high-fidelity model of the system dynamics is required. The model developed here quantifies the major environmental perturbations, and can predict the MXER tip position to within meters over one orbit.

  1. A dynamical model for the Utricularia trap

    PubMed Central

    Llorens, Coraline; Argentina, Médéric; Bouret, Yann; Marmottant, Philippe; Vincent, Olivier

    2012-01-01

    We propose a model that captures the dynamics of a carnivorous plant, Utricularia inflata. This plant possesses tiny traps for capturing small aquatic animals. Glands pump water out of the trap, yielding a negative pressure difference between the plant and its surroundings. The trap door is set into a meta-stable state and opens quickly as an extra pressure is generated by the displacement of a potential prey. As the door opens, the pressure difference sucks the animal into the trap. We write an ODE model that captures all the physics at play. We show that the dynamics of the plant is quite similar to neuronal dynamics and we analyse the effect of a white noise on the dynamics of the trap. PMID:22859569

  2. Active site fingerprinting and pharmacophore screening strategies for the identification of dual inhibitors of protein kinase C [Formula: see text] and poly (ADP-ribose) polymerase-1 (PARP-1).

    PubMed

    Chadha, Navriti; Silakari, Om

    2016-08-01

    Current clinical studies have revealed that diabetic complications are multifactorial disorders that target two or more pathways. The majority of drugs in clinical trial target aldose reductase and protein kinase C ([Formula: see text]), while recent studies disclosed a significant role played by poly (ADP-ribose) polymerase-1 (PARP-1). In light of this, the current study was aimed to identify novel dual inhibitors of [Formula: see text] and PARP-1 using a pharmaco-informatics methodology. Pharmacophore-based 3D QSAR models for these two targets were generated using HypoGen and used to screen three commercially available chemical databases to identify dual inhibitors of [Formula: see text] and PARP-1. Overall, 18 hits were obtained from the screening process; the hits were filtered based on their drug-like properties and predicted binding affinities (docking analysis). Important amino acid residues were predicted by developing a fingerprint of the active site using alanine-scanning mutagenesis and molecular dynamics. The stability of the complexes (18 hits with both proteins) and their final binding orientations were investigated using molecular dynamics simulations. Thus, novel hits have been predicted to have good binding affinities for [Formula: see text] and PARP-1 proteins, which could be further investigated for in vitro/in vivo activity. PMID:27216445

  3. Session 6: Dynamic Modeling and Systems Analysis

    NASA Technical Reports Server (NTRS)

    Csank, Jeffrey; Chapman, Jeffryes; May, Ryan

    2013-01-01

    These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

  4. Modeling of Dynamic FRC Formation

    NASA Astrophysics Data System (ADS)

    Mok, Yung; Barnes, Dan; Dettrick, Sean

    2010-11-01

    We have developed a 2-D resistive MHD code, Lamy Ridge, to simulate the entire FRC formation process in Tri Alpha's C2 device, including initial formation, translation, merging and settling into equilibrium. Two FRC's can be created simultaneously, and then translated toward each other so that they merge into a single FRC. The code couples the external circuits around the formation tubes to the partially ionized plasma inside. Plasma and neutral gas are treated as two fluids. Dynamic and energetic equations, which take into account ionization and charge exchange, are solved in a time advance manner. The geometric shape of the vessel is specified by a set of inputs that defines the boundaries, which are handled by a cut-cell algorithm in the code. Multiple external circuits and field coils can be easily added, removed or relocated through individual inputs. The design of the code is modular and flexible so that it can be applied to future devices. The results of the code are in reasonable agreement with experimental measurements on the C2 device.

  5. Dynamical Modeling of Surface Tension

    NASA Technical Reports Server (NTRS)

    Brackbill, Jeremiah U.; Kothe, Douglas B.

    1996-01-01

    In a recent review it is said that free-surface flows 'represent some of the difficult remaining challenges in computational fluid dynamics'. There has been progress with the development of new approaches to treating interfaces, such as the level-set method and the improvement of older methods such as the VOF method. A common theme of many of the new developments has been the regularization of discontinuities at the interface. One example of this approach is the continuum surface force (CSF) formulation for surface tension, which replaces the surface stress given by Laplace's equation by an equivalent volume force. Here, we describe how CSF formulation might be made more useful. Specifically, we consider a derivation of the CSF equations from a minimization of surface energy as outlined by Jacqmin (1996). This reformulation suggests that if one eliminates the computation of curvature in terms of a unit normal vector, parasitic currents may be eliminated. For this reformulation to work, it is necessary that transition region thickness be controlled. Various means for this, in addition to the one discussed by Jacqmin (1996), are discussed.

  6. Nonequilibrium dynamics in the antiferromagnetic Hubbard model

    NASA Astrophysics Data System (ADS)

    Sandri, Matteo; Fabrizio, Michele

    2013-10-01

    We investigate by means of the time-dependent Gutzwiller variational approach the out-of-equilibrium dynamics of an antiferromagnetic state evolved with the Hubbard model Hamiltonian after a sudden change of the repulsion strength U. We find that magnetic order survives more than what is expected on the basis of thermalization arguments, in agreement with recent dynamical mean field theory calculations. In addition, we find evidence of a dynamical transition for quenches to large values of U between a coherent antiferromagnet characterized by a finite quasiparticle residue to an incoherent one with vanishing residue, which finally turns into a paramagnet for even larger U.

  7. Modeling the Dynamics of Compromised Networks

    SciTech Connect

    Soper, B; Merl, D M

    2011-09-12

    Accurate predictive models of compromised networks would contribute greatly to improving the effectiveness and efficiency of the detection and control of network attacks. Compartmental epidemiological models have been applied to modeling attack vectors such as viruses and worms. We extend the application of these models to capture a wider class of dynamics applicable to cyber security. By making basic assumptions regarding network topology we use multi-group epidemiological models and reaction rate kinetics to model the stochastic evolution of a compromised network. The Gillespie Algorithm is used to run simulations under a worst case scenario in which the intruder follows the basic connection rates of network traffic as a method of obfuscation.

  8. Nonlinear Dynamic Models in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Jones, Harry

    2002-01-01

    To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

  9. Dynamical model of bubble path instability.

    PubMed

    Shew, Woodrow L; Pinton, Jean-François

    2006-10-01

    Millimeter-sized air bubbles rising through still water are known to exhibit zigzag and spiral oscillatory trajectories. We present a system of four ordinary differential equations which effectively model these dynamics. The model is based on Kirchhoff's equations and several physical arguments derived from our experimental observations. In the framework of this model, the zigzag and the spiral motions result from the same underlying bifurcation to wake instability. PMID:17155262

  10. A dynamical model for multifragmentation of nuclei

    NASA Astrophysics Data System (ADS)

    Souza, S. R.; de Paula, L.; Leray, S.; Nemeth, J.; Ngô, C.; Ngô, H.

    1994-04-01

    A schematic model based on molecular dynamics and a restructured aggregation model is presented. We apply it to study the 16O+ 80Br system at several bombarding energies and compare some of the results to available emulsion data. We find that the model reproduces the experimental charge distributions rather well and the onset of multifragmentation for this system. Some general features of nuclear multifragmentation related to charged-particle production and intermediate-mass-fragments production are discussed.

  11. Dynamic Model for Life History of Scyphozoa

    PubMed Central

    Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

    2015-01-01

    A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish. PMID:26114642

  12. Dynamic Model for Life History of Scyphozoa.

    PubMed

    Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

    2015-01-01

    A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish. PMID:26114642

  13. Modeling the dynamics of ant colony optimization.

    PubMed

    Merkle, Daniel; Middendorf, Martin

    2002-01-01

    The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants that found good solutions. The behavior of ACO algorithms and the ACO model are analyzed for certain types of permutation problems. It is shown analytically that the decisions of an ant are influenced in an intriguing way by the use of the pheromone information and the properties of the pheromone matrix. This explains why ACO algorithms can show a complex dynamic behavior even when there is only one ant per iteration and no competition occurs. The ACO model is used to describe the algorithm behavior as a combination of situations with different degrees of competition between the ants. This helps to better understand the dynamics of the algorithm when there are several ants per iteration as is always the case when using ACO algorithms for optimization. Simulations are done to compare the behavior of the ACO model with the ACO algorithm. Results show that the deterministic model describes essential features of the dynamics of ACO algorithms quite accurately, while other aspects of the algorithms behavior cannot be found in the model. PMID:12227995

  14. Dynamic modeling of speed skiing

    NASA Astrophysics Data System (ADS)

    Catalfamo, R. S.

    1997-12-01

    The equations of motion that describe a skier descending a speed-skiing hill are solved both analytically and numerically. The model is shown to agree well with actual official results but only when the hill profile is considered. A sensitivity analysis reveals which parameters most affect the skier's exit speed. Other factors, such as scaling effects and wind gusts, are included to determine whether these need to be considered in official results. One surprising result is that, under certain conditions and hill profiles, maximum skier speed is attained prior to entry into the timing zone—thus bringing into question the optimum placement of the timing gates.

  15. Dynamic modeling of solar dynamic components and systems. Final Report

    SciTech Connect

    Hochstein, J.I.; Korakianitis, T.

    1992-09-01

    The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

  16. Record Dynamics and the Parking Lot Model for granular dynamics

    NASA Astrophysics Data System (ADS)

    Sibani, Paolo; Boettcher, Stefan

    Also known for its application to granular compaction (E. Ben-Naim et al., Physica D, 1998), the Parking Lot Model (PLM) describes the random parking of identical cars in a strip with no marked bays. In the thermally activated version considered, cars can be removed at an energy cost and, in thermal equilibrium, their average density increases as temperature decreases. However, equilibration at high density becomes exceedingly slow and the system enters an aging regime induced by a kinematic constraint, the fact that parked cars may not overlap. As parking an extra car reduces the available free space,the next parking event is even harder to achieve. Records in the number of parked cars mark the salient features of the dynamics and are shown to be well described by the log-Poisson statistics known from other glassy systems with record dynamics. Clusters of cars whose positions must be rearranged to make the next insertion possible have a length scale which grows logarithmically with age, while their life-time grows exponentially with size. The implications for a recent cluster model of colloidal dynamics,(S. Boettcher and P. Sibani, J. Phys.: Cond. Matter, 2011 N. Becker et al., J. Phys.: Cond. Matter, 2014) are discussed. Support rom the Villum Foundation is gratefully acknowledged.

  17. Dynamic Modeling of Solar Dynamic Components and Systems

    NASA Technical Reports Server (NTRS)

    Hochstein, John I.; Korakianitis, T.

    1992-01-01

    The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

  18. Quantum model for the price dynamics

    NASA Astrophysics Data System (ADS)

    Choustova, Olga

    2008-10-01

    We apply methods of quantum mechanics to mathematical modelling of price dynamics in a financial market. We propose to describe behavioral financial factors (e.g., expectations of traders) by using the pilot wave (Bohmian) model of quantum mechanics. Our model is a quantum-like model of the financial market, cf. with works of W. Segal, I.E. Segal, E. Haven. In this paper we study the problem of smoothness of price-trajectories in the Bohmian financial model. We show that even the smooth evolution of the financial pilot wave [psi](t,x) (representing expectations of traders) can induce jumps of prices of shares.

  19. Efficient dynamic models of tensegrity systems

    NASA Astrophysics Data System (ADS)

    Skelton, Robert

    2009-03-01

    The multi-body dynamics appear in a new form, as a matrix differential equation, rather than the traditional vector differential equation. The model has a constant mass matrix, and the equations are non-minimal. A specific focus of this paper is tensegrity systems. A tensegrity system requires prestress for stabilization of the configuration of rigid bodies and tensile members. This paper provides an efficient model for both static and dynamic behavior of such systems, specialized for the case when the rigid bodies are axi-symmetric rods.

  20. Modeling emotional dynamics : currency versus field.

    SciTech Connect

    Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago

    2008-08-01

    Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.

  1. Dynamic Radiation Environment Assimilation Model: DREAM

    NASA Astrophysics Data System (ADS)

    Reeves, G. D.; Chen, Y.; Cunningham, G. S.; Friedel, R. W. H.; Henderson, M. G.; Jordanova, V. K.; Koller, J.; Morley, S. K.; Thomsen, M. F.; Zaharia, S.

    2012-03-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) was developed to provide accurate, global specification of the Earth's radiation belts and to better understand the physical processes that control radiation belt structure and dynamics. DREAM is designed using a modular software approach in order to provide a computational framework that makes it easy to change components such as the global magnetic field model, radiation belt dynamics model, boundary conditions, etc. This paper provides a broad overview of the DREAM model and a summary of some of the principal results to date. We describe the structure of the DREAM model, describe the five major components, and illustrate the various options that are available for each component. We discuss how the data assimilation is performed and the data preprocessing and postprocessing that are required for producing the final DREAM outputs. We describe how we apply global magnetic field models for conversion between flux and phase space density and, in particular, the benefits of using a self-consistent, coupled ring current-magnetic field model. We discuss some of the results from DREAM including testing of boundary condition assumptions and effects of adding a source term to radial diffusion models. We also describe some of the testing and validation of DREAM and prospects for future development.

  2. Optimal Empirical Prognostic Models of Climate Dynamics

    NASA Astrophysics Data System (ADS)

    Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A. M.

    2014-12-01

    In this report the empirical methodology for prediction of climate dynamics is suggested. We construct the dynamical models of data patterns connected with climate indices, from observed spatially distributed time series. The models are based on artificial neural network (ANN) parameterization and have a form of discrete stochastic evolution operator mapping some sequence of systems state on the next one [1]. Different approaches to reconstruction of empirical basis (phase variables) for system's phase space representation, which is appropriate for forecasting the climate index of interest, are discussed in the report; for this purpose both linear and non-linear data expansions are considered. The most important point of the methodology is finding the optimal structural parameters of the model such as dimension of variable vector, i.e. number of principal components used for modeling, the time lag used for prediction, and number of neurons in ANN determining the quality of approximation. Actually, we need to solve the model selection problem, i.e. we want to obtain a model of optimal complexity in relation to analyzed time series. We use MDL approach [2] for this purpose: the model providing best data compression is chosen. The method is applied to space-distributed time-series of sea surface temperature and sea level pressure taken from IRI datasets [3]: the ability of proposed models to predict different climate indices (incl. Multivariate ENSO index, Pacific Decadal Oscillation index, North-Atlantic Oscillation index) is investigated. References:1. Molkov Ya. I., E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, Random dynamical models from time series. Phys. Rev. E, 85, 036216, 2012.2. Molkov, Ya.I., D.N. Mukhin, E.M. Loskutov, A.M. Feigin, and G.A. Fidelin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series. Phys. Rev. E, 80, 046207, 2009.3. IRI/LDEO Climate Data Library (http://iridl.ldeo.columbia.edu/)

  3. Protein-ligand-based pharmacophores: generation and utility assessment in computational ligand profiling.

    PubMed

    Meslamani, Jamel; Li, Jiabo; Sutter, Jon; Stevens, Adrian; Bertrand, Hugues-Olivier; Rognan, Didier

    2012-04-23

    Ligand profiling is an emerging computational method for predicting the most likely targets of a bioactive compound and therefore anticipating adverse reactions, side effects and drug repurposing. A few encouraging successes have already been reported using ligand 2-D similarity searches and protein-ligand docking. The current study describes the use of receptor-ligand-derived pharmacophore searches as a tool to link ligands to putative targets. A database of 68,056 pharmacophores was first derived from 8,166 high-resolution protein-ligand complexes. In order to limit the number of queries, a maximum of 10 pharmacophores was generated for each complex according to their predicted selectivity. Pharmacophore search was compared to ligand-centric (2-D and 3-D similarity searches) and docking methods in profiling a set of 157 diverse ligands against a panel of 2,556 unique targets of known X-ray structure. As expected, ligand-based methods outperformed, in most of the cases, structure-based approaches in ranking the true targets among the top 1% scoring entries. However, we could identify ligands for which only a single method was successful. Receptor-ligand-based pharmacophore search is notably a fast and reliable alternative to docking when few ligand information is available for some targets. Overall, the present study suggests that a workflow using the best profiling method according to the protein-ligand context is the best strategy to follow. We notably present concrete guidelines for selecting the optimal computational method according to simple ligand and binding site properties. PMID:22480372

  4. A Novel Virus-Patch Dynamic Model.

    PubMed

    Yang, Lu-Xing; Yang, Xiaofan

    2015-01-01

    The distributed patch dissemination strategies are a promising alternative to the conventional centralized patch dissemination strategies. This paper aims to establish a theoretical framework for evaluating the effectiveness of distributed patch dissemination mechanism. Assuming that the Internet offers P2P service for every pair of nodes on the network, a dynamic model capturing both the virus propagation mechanism and the distributed patch dissemination mechanism is proposed. This model takes into account the infected removable storage media and hence captures the interaction of patches with viruses better than the original SIPS model. Surprisingly, the proposed model exhibits much simpler dynamic properties than the original SIPS model. Specifically, our model admits only two potential (viral) equilibria and undergoes a fold bifurcation. The global stabilities of the two equilibria are determined. Consequently, the dynamical properties of the proposed model are fully understood. Furthermore, it is found that reducing the probability per unit time of disconnecting a node from the Internet benefits the containment of electronic viruses. PMID:26368556

  5. A Novel Virus-Patch Dynamic Model

    PubMed Central

    Yang, Lu-Xing; Yang, Xiaofan

    2015-01-01

    The distributed patch dissemination strategies are a promising alternative to the conventional centralized patch dissemination strategies. This paper aims to establish a theoretical framework for evaluating the effectiveness of distributed patch dissemination mechanism. Assuming that the Internet offers P2P service for every pair of nodes on the network, a dynamic model capturing both the virus propagation mechanism and the distributed patch dissemination mechanism is proposed. This model takes into account the infected removable storage media and hence captures the interaction of patches with viruses better than the original SIPS model. Surprisingly, the proposed model exhibits much simpler dynamic properties than the original SIPS model. Specifically, our model admits only two potential (viral) equilibria and undergoes a fold bifurcation. The global stabilities of the two equilibria are determined. Consequently, the dynamical properties of the proposed model are fully understood. Furthermore, it is found that reducing the probability per unit time of disconnecting a node from the Internet benefits the containment of electronic viruses. PMID:26368556

  6. Modeling biological pathway dynamics with timed automata.

    PubMed

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience. PMID:24808226

  7. Polarizable protein model for Dissipative Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Peter, Emanuel; Lykov, Kirill; Pivkin, Igor

    2015-11-01

    In this talk, we present a novel polarizable protein model for the Dissipative Particle Dynamics (DPD) simulation technique, a coarse-grained particle-based method widely used in modeling of fluid systems at the mesoscale. We employ long-range electrostatics and Drude oscillators in combination with a newly developed polarizable water model. The protein in our model is resembled by a polarizable backbone and a simplified representation of the sidechains. We define the model parameters using the experimental structures of 2 proteins: TrpZip2 and TrpCage. We validate the model on folding of five other proteins and demonstrate that it successfully predicts folding of these proteins into their native conformations. As a perspective of this model, we will give a short outlook on simulations of protein aggregation in the bulk and near a model membrane, a relevant process in several Amyloid diseases, e.g. Alzheimer's and Diabetes II.

  8. System and mathematical modeling of quadrotor dynamics

    NASA Astrophysics Data System (ADS)

    Goodman, Jacob M.; Kim, Jinho; Gadsden, S. Andrew; Wilkerson, Stephen A.

    2015-05-01

    Unmanned aerial systems (UAS) are becoming increasingly visible in our daily lives; and range in operation from search and rescue, monitoring hazardous environments, and to the delivery of goods. One of the most popular UAS are based on a quad-rotor design. These are typically small devices that rely on four propellers for lift and movement. Quad-rotors are inherently unstable, and rely on advanced control methodologies to keep them operating safely and behaving in a predictable and desirable manner. The control of these devices can be enhanced and improved by making use of an accurate dynamic model. In this paper, we examine a simple quadrotor model, and note some of the additional dynamic considerations that were left out. We then compare simulation results of the simple model with that of another comprehensive model.

  9. Dynamic model of the Earth's upper atmosphere

    NASA Technical Reports Server (NTRS)

    Slowey, J. W.

    1984-01-01

    An initial modification to the MSF/J70 Thermospheric Model, in which the variations due to sudden geomagnetic disturbances upon the Earth's upper atmospheric density structure were modeled is presented. This dynamic model of the geomagnetic variation included is an improved version of one which SAO developed from the analysis of the ESRO 4 mass spectrometer data that was incorporated in the Jacchia 1977 model. The variation with geomagnetic local time as well as with geomagnetic latitude are included, and also the effects due to disturbance of the temperature profiles in the region of energy deposition.

  10. Modeling the Hydrogen Bond within Molecular Dynamics

    ERIC Educational Resources Information Center

    Lykos, Peter

    2004-01-01

    The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.

  11. DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING

    EPA Science Inventory

    The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...

  12. Model Of Neural Network With Creative Dynamics

    NASA Technical Reports Server (NTRS)

    Zak, Michail; Barhen, Jacob

    1993-01-01

    Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.

  13. Population mixture model for nonlinear telomere dynamics

    NASA Astrophysics Data System (ADS)

    Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

    2008-12-01

    Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

  14. Modeling of dynamical processes in laser ablation

    SciTech Connect

    Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.

    1995-12-31

    Various physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed-laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume, plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms, hydrodynamic and collisional descriptions of plume transport, and molecular dynamics models of the interaction of plume particles with the deposition substrate.

  15. Feature extraction for structural dynamics model validation

    SciTech Connect

    Hemez, Francois; Farrar, Charles; Park, Gyuhae; Nishio, Mayuko; Worden, Keith; Takeda, Nobuo

    2010-11-08

    This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

  16. Dynamic models for the study of frailty.

    PubMed

    Lipsitz, Lewis A

    2008-11-01

    Frailty can be viewed as resulting from the degradation of multiple interacting physiologic systems that are normally responsible for healthy adaptation to the daily demands of life. Mathematical models that can quantify alterations in the dynamics of physiologic systems and their interactions may help characterize the syndrome of frailty and enable investigators to test interventions to prevent its onset. One theoretical mathematical model reported by Varadhan et al. in this issue of the Journal represents one type of regulatory process that may become altered in frail individuals-the stimulus-response mechanism [Varadhan, R., Seplaki, C.S., Xue, Q.L., Bandeen-Roche, K., Fried, L.P. Stimulus-response paradigm for characterizing the loss of resilience in homeostatic regulation associated with frailty. Mech. Ageing Dev., this issue]. This model focuses on the timing of recovery from a single stimulus, rather than the full array of responses that might be altered in a complex dynamical system. Therefore, alternative models are needed to describe the wide variety of behaviors of physiologic systems over time and how they change with the onset of frailty. One such model, based on a simple signaling network composed of a lattice of nodes and the bi-directional connections between them, can reproduce the complex, fractal-like nature of healthy physiological processes. This model can be used to demonstrate how the degradation of signaling pathways within a physiologic system can result in the loss of complex dynamics that characterizes frailty. PMID:18930754

  17. Rupture dynamics in model polymer systems.

    PubMed

    Borah, Rupam; Debnath, Pallavi

    2016-05-11

    In this paper we explore the rupture dynamics of a model polymer system to capture the microscopic mechanism during relative motion of surfaces at the single polymer level. Our model is similar to the model for friction introduced by Filippov, Klafter, and Urbakh [Filippov et al., Phys. Rev. Lett., 2004, 92, 135503]; but with an important generalization to a flexible transducer (modelled as a bead spring polymer) which is attached to a fixed rigid planar substrate by interconnecting bonds (modelled as harmonic springs), and pulled by a constant force FT. Bonds are allowed to rupture stochastically. The model is simulated, and the results for a certain set of parameters exhibit a sequential rupture mechanism resulting in rupture fronts. A mean field formalism is developed to study these rupture fronts and the possible propagating solutions for the coupled bead and bond dynamics, where the coupling excludes an exact analytical treatment. Numerical solutions to mean field equations are obtained by standard numerical techniques, and they agree well with the simulation results which show sequential rupture. Within a travelling wave formalism based on the Tanh method, we show that the velocity of the rupture front can be obtained in closed form. The derived expression for the rupture front velocity gives good agreement with the stochastic and mean field results, when the rupture is sequential, while propagating solutions for bead and bond dynamics are shown to agree under certain conditions. PMID:27087684

  18. Nonsmooth dynamics in spiking neuron models

    NASA Astrophysics Data System (ADS)

    Coombes, S.; Thul, R.; Wedgwood, K. C. A.

    2012-11-01

    Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage

  19. Condensed Antenna Structural Models for Dynamics Analysis

    NASA Technical Reports Server (NTRS)

    Levy, R.

    1985-01-01

    Condensed degree-of-freedom models are compared with large degree-of-freedom finite-element models of a representative antenna-tipping and alidade structure, for both locked and free-rotor configurations. It is shown that: (1) the effective-mass models accurately reproduce the lower-mode natural frequencies of the finite element model; (2) frequency responses for the two types of models are in agreement up to at least 16 rad/s for specific points; and (3) transient responses computed for the same points are in good agreement. It is concluded that the effective-mass model, which best represents the five lower modes of the finite-element model, is a sufficient representation of the structure for future incorporation with a total servo control structure dynamic simulation.

  20. Dynamic occupancy models for explicit colonization processes.

    PubMed

    Broms, Kristin M; Hooten, Mevin B; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

    2016-01-01

    The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations. PMID:27008788

  1. Dynamic occupancy models for explicit colonization processes

    USGS Publications Warehouse

    Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

    2016-01-01

    The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.

  2. Direct modeling for computational fluid dynamics

    NASA Astrophysics Data System (ADS)

    Xu, Kun

    2015-06-01

    All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct

  3. Dynamics of macroautophagy: Modeling and oscillatory behavior

    NASA Astrophysics Data System (ADS)

    Han, Kyungreem; Kwon, Hyun Woong; Kang, Hyuk; Kim, Jinwoong; Lee, Myung-Shik; Choi, M. Y.

    2012-02-01

    We propose a model for macroautophagy and study the resulting dynamics of autophagy in a system isolated from its extra-cellular environment. It is found that the intracellular concentrations of autophagosomes and autolysosomes display oscillations with their own natural frequencies. Such oscillatory behaviors, which are interrelated to the dynamics of intracellular ATP, amino acids, and proteins, are consistent with the very recent biological observations. Implications of this theoretical study of autophagy are discussed, with regard to the possibility of guiding molecular studies of autophagy.

  4. SORD: A New Rupture Dynamics Modeling Code

    NASA Astrophysics Data System (ADS)

    Ely, G.; Minster, B.; Day, S.

    2005-12-01

    We report on our progress in validating our rupture dynamics modeling code, capable of dealing with nonplanar faults and surface topography. The method uses a "mimetic" approach to model spontaneous rupture on a fault within a 3D isotropic anelastic solid, wherein the equations of motion are approximated with a second order Support-Operator method on a logically rectangular mesh. Grid cells are not required to be parallelepipeds, however, so that non-rectangular meshes can be supported to model complex regions. However, for areas in the mesh which are in fact rectangular, the code uses a streamlined version of the algorithm that takes advantage of the simplifications of the operators in such areas. The fault itself is modeled using a double node technique, and the rheology on the fault surface is modeled through a slip-weakening, frictional, internal boundary condition. The Support Operator Rupture Dynamics (SORD) code, was prototyped in MATLAB, and all algorithms have been validated against known (including analytical solutions, eg Kostrov, 1964) solutions or previously validated solutions. This validation effort is conducted in the context of the SCEC Dynamic Rupture model validation effort led by R. Archuleta and R. Harris. Absorbing boundaries at the model edges are handled using the perfectly matched layers method (PML) (Olsen & Marcinkovich, 2003). PML is shown to work extremely well on rectangular meshes. We show that our implementation is also effective on non-rectangular meshes under the restriction that the boundary be planar. For validation of the model we use a variety of test cases using two types of meshes: a rectangular mesh and skewed mesh. The skewed mesh amplifies any biases caused by the Support-Operator method on non-rectangular elements. Wave propagation and absorbing boundaries are tested with a spherical wave source. Rupture dynamics on a planar fault are tested against (1) a Kostrov analytical solution, (2) data from foam rubber scale models

  5. The dynamic modelling of a slotted test section

    NASA Technical Reports Server (NTRS)

    Gumas, G.

    1979-01-01

    A mathematical model of the wind tunnel dynamics was developed. The modelling techniques were restricted to the use of one dimensional unsteady flow. The dynamic characteristics of slotted test section incorporated into the model are presented.

  6. Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

    EPA Science Inventory

    The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

  7. Molecular insights of protein contour recognition with ligand pharmacophoric sites through combinatorial library design and MD simulation in validating HTLV-1 PR inhibitors.

    PubMed

    Selvaraj, Chandrabose; Omer, Ankur; Singh, Poonam; Singh, Sanjeev Kumar

    2015-01-01

    Retroviruses HIV-1 and HTLV-1 are chiefly considered to be the most dangerous pathogens in Homo sapiens. These two viruses have structurally unique protease (PR) enzymes, which are having common function of its replication mechanism. Though HIV PR drugs failed to inhibit HTLV-1 infections, they emphatically emphasise the need for designing new lead compounds against HTLV-1 PR. Therefore, we tried to understand the binding level interactions through the charge environment present in both ligand and protein active sites. The domino effect illustrates that libraries of purvalanol-A are attuned to fill allosteric binding site of HTLV-1 PR through molecular recognition and shows proper binding of ligand pharmacophoric features in receptor contours. Our screening evaluates seven compounds from purvalanol-A libraries, and these compounds' pharmacophore searches for an appropriate place in the binding site and it places well according to respective receptor contour surfaces. Thus our result provides a platform for the progress of more effective compounds, which are better in free energy calculation, molecular docking, ADME and molecular dynamics studies. Finally, this research provided novel chemical scaffolds for HTLV-1 drug discovery. PMID:25335799

  8. Collisional model for granular impact dynamics.

    PubMed

    Clark, Abram H; Petersen, Alec J; Behringer, Robert P

    2014-01-01

    When an intruder strikes a granular material from above, the grains exert a stopping force which decelerates and stops the intruder. Many previous studies have used a macroscopic force law, including a drag force which is quadratic in velocity, to characterize the decelerating force on the intruder. However, the microscopic origins of the force-law terms are still a subject of debate. Here, drawing from previous experiments with photoelastic particles, we present a model which describes the velocity-squared force in terms of repeated collisions with clusters of grains. From our high speed photoelastic data, we infer that "clusters" correspond to segments of the strong force network that are excited by the advancing intruder. The model predicts a scaling relation for the velocity-squared drag force that accounts for the intruder shape. Additionally, we show that the collisional model predicts an instability to rotations, which depends on the intruder shape. To test this model, we perform a comprehensive experimental study of the dynamics of two-dimensional granular impacts on beds of photoelastic disks, with different profiles for the leading edge of the intruder. We particularly focus on a simple and useful case for testing shape effects by using triangular-nosed intruders. We show that the collisional model effectively captures the dynamics of intruder deceleration and rotation; i.e., these two dynamical effects can be described as two different manifestations of the same grain-scale physical processes. PMID:24580216

  9. Electronic continuum model for molecular dynamics simulations.

    PubMed

    Leontyev, I V; Stuchebrukhov, A A

    2009-02-28

    A simple model for accounting for electronic polarization in molecular dynamics (MD) simulations is discussed. In this model, called molecular dynamics electronic continuum (MDEC), the electronic polarization is treated explicitly in terms of the electronic continuum (EC) approximation, while the nuclear dynamics is described with a fixed-charge force field. In such a force-field all atomic charges are scaled to reflect the screening effect by the electronic continuum. The MDEC model is rather similar but not equivalent to the standard nonpolarizable force-fields; the differences are discussed. Of our particular interest is the calculation of the electrostatic part of solvation energy using standard nonpolarizable MD simulations. In a low-dielectric environment, such as protein, the standard MD approach produces qualitatively wrong results. The difficulty is in mistreatment of the electronic polarizability. We show how the results can be much improved using the MDEC approach. We also show how the dielectric constant of the medium obtained in a MD simulation with nonpolarizable force-field is related to the static (total) dielectric constant, which includes both the nuclear and electronic relaxation effects. Using the MDEC model, we discuss recent calculations of dielectric constants of alcohols and alkanes, and show that the MDEC results are comparable with those obtained with the polarizable Drude oscillator model. The applicability of the method to calculations of dielectric properties of proteins is discussed. PMID:19256627

  10. Continuum modeling of cooperative traffic flow dynamics

    NASA Astrophysics Data System (ADS)

    Ngoduy, D.; Hoogendoorn, S. P.; Liu, R.

    2009-07-01

    This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.

  11. Global dynamic modeling of a transmission system

    NASA Astrophysics Data System (ADS)

    Choy, F. K.; Qian, W.

    1993-04-01

    The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.

  12. Global dynamic modeling of a transmission system

    NASA Technical Reports Server (NTRS)

    Choy, F. K.; Qian, W.

    1993-01-01

    The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.

  13. Development of a dynamic thermal model process

    SciTech Connect

    Smith, F. R.

    1996-04-01

    A dynamic electrical-thermal modeling simulation technique was developed to allow up-front design of thermal and electronic packaging with a high degree of accuracy and confidence. We are developing a hybrid multichip module output driver which controls with power MOSFET driver circuits. These MOSFET circuits will dissipate from 13 to 26 watts per driver in a physical package less than two square inches. The power dissipation plus an operating temperature range of -55{degrees} C to 100{degrees} C makes an accurate thermal package design critical. The project goal was to develop a simulation process to dynamically model the electrical/thermal characteristics of the power MOSFETS using the SABER analog simulator and the ABAQUS finite element simulator. SABER would simulate the electrical characteristics of the multi-chip module design while co-simulation is being done with ABAQUS simulating the solid model thermal characteristics of the MOSFET package. The dynamic parameters, MOSFET power and chip temperature, would be actively passed between simulators to effect a coupled simulator modelling technique. The project required a development of a SABER late for the analog ASIC controller circuit, a dynamic electrical/thermal template for the IRF150 and IRF9130 power MOSFETs, a solid model of the multi-chip module package, FORTRAN code to handle I/Q between and HP755 workstation and SABER, and I/O between CRAY J90 computer and ABAQUS. The simulation model was certified by measured electrical characteristics of the circuits and real time thermal imaging of the output multichip module.

  14. Overview of the GRC Stirling Convertor System Dynamic Model

    NASA Technical Reports Server (NTRS)

    Lewandowski, Edward J.; Regan, Timothy F.

    2004-01-01

    A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

  15. Fluid-dynamical model for antisurfactants

    NASA Astrophysics Data System (ADS)

    Conn, Justin J. A.; Duffy, Brian R.; Pritchard, David; Wilson, Stephen K.; Halling, Peter J.; Sefiane, Khellil

    2016-04-01

    We construct a fluid-dynamical model for the flow of a solution with a free surface at which surface tension acts. This model can describe both classical surfactants, which decrease the surface tension of the solution relative to that of the pure solvent, and antisurfactants (such as many salts when added to water, and small amounts of water when added to alcohol) which increase it. We demonstrate the utility of the model by considering the linear stability of an infinitely deep layer of initially quiescent fluid. In particular, we predict the occurrence of an instability driven by surface-tension gradients, which occurs for antisurfactant, but not for surfactant, solutions.

  16. Informations in Models of Evolutionary Dynamics

    NASA Astrophysics Data System (ADS)

    Rivoire, Olivier

    2016-03-01

    Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.

  17. Polarizable water model for Dissipative Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Pivkin, Igor; Peter, Emanuel

    2015-11-01

    Dissipative Particle Dynamics (DPD) is an efficient particle-based method for modeling mesoscopic behavior of fluid systems. DPD forces conserve the momentum resulting in a correct description of hydrodynamic interactions. Polarizability has been introduced into some coarse-grained particle-based simulation methods; however it has not been done with DPD before. We developed a new polarizable coarse-grained water model for DPD, which employs long-range electrostatics and Drude oscillators. In this talk, we will present the model and its applications in simulations of membrane systems, where polarization effects play an essential role.

  18. Dynamical Field Model of Hand Preference

    NASA Astrophysics Data System (ADS)

    Franceschetti, Donald R.; Cantalupo, Claudio

    2000-11-01

    Dynamical field models of information processing in the nervous system are being developed by a number of groups of psychologists and physicists working together to explain The details of behaviors exhibited by a number of animal species. Here we adapt such a model to the expression of hand preference in a small primate, the bushbaby (Otolemur garnetti) . The model provides a theoretical foundation for the interpretation of an experiment currently underway in which a several of these animals are forced to extend either right or left hand to retrieve a food item from a rotating turntable.

  19. A computational model for dynamic vision

    NASA Technical Reports Server (NTRS)

    Moezzi, Saied; Weymouth, Terry E.

    1990-01-01

    This paper describes a novel computational model for dynamic vision which promises to be both powerful and robust. Furthermore the paradigm is ideal for an active vision system where camera vergence changes dynamically. Its basis is the retinotopically indexed object-centered encoding of the early visual information. Specifically, the relative distances of objects to a set of referents is encoded in image registered maps. To illustrate the efficacy of the method, it is applied to the problem of dynamic stereo vision. Integration of depth information over multiple frames obtained by a moving robot generally requires precise information about the relative camera position from frame to frame. Usually, this information can only be approximated. The method facilitates the integration of depth information without direct use or knowledge of camera motion.

  20. Structural system identification: Structural dynamics model validation

    SciTech Connect

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  1. Dynamic Multicriteria Evaluation of Conceptual Hydrological Models

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H.; Fenicia, F.; Gupta, H. V.

    2007-12-01

    Accurate and precise forecasts of river streamflows are crucial for successful management of water resources and under the threat of hydrological extremes such as floods and droughts. Conceptual rainfall-runoff models are the most popular approach in flood forecasting. However, the calibration and evaluation of such models is often oversimplified by the use of performance statistics that largely ignore the dynamic character of a watershed system. This research aims to find novel ways of model evaluation by identifying periods of hydrologic similarity and customizing evaluation within each period using multiple criteria. A dynamic approach to hydrologic model identification, calibration and testing can be realized by applying clustering algorithms (e.g., Self-Organizing Map, Fuzzy C-means algorithm) to hydrological data. These algorithms are able to identify clusters in the data that represent periods of hydrological similarity. In this way, dynamic catchment system behavior can be simplified within the clusters that are identified. Although clustering requires a number of subjective choices, new insights into the hydrological functioning of a catchment can be obtained. Finally, separate model multi-criteria calibration and evaluation is performed for each of the clusters. Such a model evaluation procedure shows to be reliable and gives much-needed feedback on exactly where certain model structures fail. Several clustering algorithms were tested on two data sets of meso-scale and large-scale catchments. The results show that the clustering algorithms define categories that reflect hydrological process understanding: dry/wet seasons, rising/falling hydrograph limbs, precipitation-driven/ non-driven periods, etc. The results of various clustering algorithms are compared and validated using expert knowledge. Calibration results on a conceptual hydrological model show that the common practice of single-criteria calibration over the complete time series fails to perform

  2. Dynamic alignment models for neural coding.

    PubMed

    Kollmorgen, Sepp; Hahnloser, Richard H R

    2014-03-01

    Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

  3. Cellular automata modelling of biomolecular networks dynamics.

    PubMed

    Bonchev, D; Thomas, S; Apte, A; Kier, L B

    2010-01-01

    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  4. Efficient gradient computation for dynamical models

    PubMed Central

    Sengupta, B.; Friston, K.J.; Penny, W.D.

    2014-01-01

    Data assimilation is a fundamental issue that arises across many scales in neuroscience — ranging from the study of single neurons using single electrode recordings to the interaction of thousands of neurons using fMRI. Data assimilation involves inverting a generative model that can not only explain observed data but also generate predictions. Typically, the model is inverted or fitted using conventional tools of (convex) optimization that invariably extremise some functional — norms, minimum descriptive length, variational free energy, etc. Generally, optimisation rests on evaluating the local gradients of the functional to be optimized. In this paper, we compare three different gradient estimation techniques that could be used for extremising any functional in time — (i) finite differences, (ii) forward sensitivities and a method based on (iii) the adjoint of the dynamical system. We demonstrate that the first-order gradients of a dynamical system, linear or non-linear, can be computed most efficiently using the adjoint method. This is particularly true for systems where the number of parameters is greater than the number of states. For such systems, integrating several sensitivity equations – as required with forward sensitivities – proves to be most expensive, while finite-difference approximations have an intermediate efficiency. In the context of neuroimaging, adjoint based inversion of dynamical causal models (DCMs) can, in principle, enable the study of models with large numbers of nodes and parameters. PMID:24769182

  5. Activated Dynamics in Dense Model Nanocomposites

    NASA Astrophysics Data System (ADS)

    Xie, Shijie; Schweizer, Kenneth

    The nonlinear Langevin equation approach is applied to investigate the ensemble-averaged activated dynamics of small molecule liquids (or disconnected segments in a polymer melt) in dense nanocomposites under model isobaric conditions where the spherical nanoparticles are dynamically fixed. Fully thermalized and quenched-replica integral equation theory methods are employed to investigate the influence on matrix dynamics of the equilibrium and nonequilibrium nanocomposite structure, respectively. In equilibrium, the miscibility window can be narrow due to depletion and bridging attraction induced phase separation which limits the study of activated dynamics to regimes where the barriers are relatively low. In contrast, by using replica integral equation theory, macroscopic demixing is suppressed, and the addition of nanoparticles can induce much slower activated matrix dynamics which can be studied over a wide range of pure liquid alpha relaxation times, interfacial attraction strengths and ranges, particle sizes and loadings, and mixture microstructures. Numerical results for the mean activated relaxation time, transient localization length, matrix elasticity and kinetic vitrification in the nanocomposite will be presented.

  6. Dynamic Modeling of an Evapotranspiration Cap

    SciTech Connect

    Jacob J. Jacobson; Steven Piet; Rafael Soto; Gerald Sehlke; Harold Heydt; John Visser

    2005-10-01

    The U.S. Department of Energy is scheduled to design and install hundreds of landfill caps/barriers over the next several decades and these caps will have a design life expectancy of up to 1,000 years. Other landfill caps with 30 year design lifetimes are reaching the end of their original design life; the changes to these caps need to be understood to provide a basis for lifetime extension. Defining the attributes that make a successful cap (one that isolates the waste from the environment) is crucial to these efforts. Because cap systems such as landfill caps are dynamic in nature, it is impossible to understand, monitor, and update lifetime predictions without understanding the dynamics of cap degradation, which is most often due to multiple interdependent factors rather than isolated independent events. In an attempt to understand the dynamics of cap degradation, a computer model using system dynamics is being developed to capture the complex behavior of an evapotranspiration cap. The specific objectives of this project are to capture the dynamic, nonlinear feedback loop structures underlying an evapotranspiration cap and, through computer simulation, gain a better understanding of long-term behavior, influencing factors, and, ultimately, long-term cap performance.

  7. Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

    NASA Astrophysics Data System (ADS)

    Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

    2016-04-01

    Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343

  8. Pharmacophore Elucidation and Molecular Docking Studies on 5-Phenyl-1-(3-pyridyl)-1H-1,2,4-triazole-3-carboxylic Acid Derivatives as COX-2 Inhibitors

    PubMed Central

    Lindner, Marc; Sippl, Wolfgang; Radwan, Awwad A.

    2010-01-01

    A set of 5-phenyl-1-(3-pyridyl)-1H-1,2,4-triazole-3-carboxylic acid derivatives (16–32) showing anti-inflammatory activity was analyzed using a three-dimensional qualitative structure-selectivity relationship (3D QSSR) method. The CatalystHipHop approach was used to generate a pharmacophore model for cyclooxygenase-2 (COX-2) inhibitors based on a training set of 15 active inhibitors (1–15). The degree of fitting of the test set compounds (16–32) to the generated hypothetical model revealed a qualitative measure of the more or less selective COX-2 inhibition of these compounds. The results indicate that most derivatives (16, 18, 20–25, and 30–32) are able to effectively satisfy the proposed pharmacophore geometry using energy accessible conformers (Econf < 20 kcal/mol). In addition, the triazole derivatives (16–32) were docked into COX-1 and COX-2 X-ray structures, using the program GOLD. Based on the docking results it is suggested that several of these novel triazole derivatives are active COX inhibitors with a significant preference for COX-2. In principle, this work presents an interesting, comprehensive approach to theoretically predict the mode of action of compounds that showed anti-inflammatory activity in an in vivo model. PMID:21179343

  9. Modelling the mechanoreceptor’s dynamic behaviour

    PubMed Central

    Song, Zhuoyi; Banks, Robert W; Bewick, Guy S

    2015-01-01

    All sensory receptors adapt, i.e. they constantly adjust their sensitivity to external stimuli to match the current demands of the natural environment. Electrophysiological responses of sensory receptors from widely different modalities seem to exhibit common features related to adaptation, and these features can be used to examine the underlying sensory transduction mechanisms. Among the principal senses, mechanosensation remains the least understood at the cellular level. To gain greater insights into mechanosensory signalling, we investigated if mechanosensation displayed adaptive dynamics that could be explained by similar biophysical mechanisms in other sensory modalities. To do this, we adapted a fly photoreceptor model to describe the primary transduction process for a stretch-sensitive mechanoreceptor, taking into account the viscoelastic properties of the accessory muscle fibres and the biophysical properties of known mechanosensitive channels (MSCs). The model’s output is in remarkable agreement with the electrical properties of a primary ending in an isolated decapsulated spindle; ramp-and-hold stretch evokes a characteristic pattern of potential change, consisting of a large dynamic depolarization during the ramp phase and a smaller static depolarization during the hold phase. The initial dynamic component is likely to be caused by a combination of the mechanical properties of the muscle fibres and a refractory state in the MSCs. Consistent with the literature, the current model predicts that the dynamic component is due to a rapid stress increase during the ramp. More novel predictions from the model are the mechanisms to explain the initial peak in the dynamic component. At the onset of the ramp, all MSCs are sensitive to external stimuli, but as they become refractory (inactivated), fewer MSCs are able to respond to the continuous stretch, causing a sharp decrease after the peak response. The same mechanism could contribute a faster component in

  10. Three-dimensional pharmacophore design and biochemical screening identifies substituted 1,2,4-triazoles as inhibitors of the annexin A2-S100A10 protein interaction.

    PubMed

    Reddy, Tummala R K; Li, Chan; Fischer, Peter M; Dekker, Lodewijk V

    2012-08-01

    Protein interactions are increasingly appreciated as targets in small-molecule drug discovery. The interaction between the adapter protein S100A10 and its binding partner annexin A2 is a potentially important drug target. To obtain small-molecule starting points for inhibitors of this interaction, a three-dimensional pharmacophore model was constructed from the X-ray crystal structure of the complex between S100A10 and annexin A2. The pharmacophore model represents the favourable hydrophobic and hydrogen bond interactions between the two partners, as well as spatial and receptor site constraints (excluded volume spheres). Using this pharmacophore model, UNITY flex searches were carried out on a 3D library of 0.7 million commercially available compounds. This resulted in 568 hit compounds. Subsequently, GOLD docking studies were performed on these hits, and a set of 190 compounds were purchased and tested biochemically for inhibition of the protein interaction. Three compounds of similar chemical structure were identified as genuine inhibitors of the binding of annexin A2 to S100A10. The binding modes predicted by GOLD were in good agreement with their UNITY-generated conformations. We synthesised a series of analogues revealing areas critical for binding. Thus computational predictions and biochemical screening can be used successfully to derive novel chemical classes of protein-protein interaction blockers. PMID:22644793

  11. Dynamical Causal Modeling from a Quantum Dynamical Perspective

    NASA Astrophysics Data System (ADS)

    Demiralp, Emre; Demiralp, Metin

    2010-09-01

    Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called "Quantum Harmonical Form (QHF)". QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, this limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.

  12. Dynamical Causal Modeling from a Quantum Dynamical Perspective

    SciTech Connect

    Demiralp, Emre; Demiralp, Metin

    2010-09-30

    Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, this limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.

  13. Identification of helicopter rotor dynamic models

    NASA Technical Reports Server (NTRS)

    Molusis, J. A.; Bar-Shalom, Y.; Warmbrodt, W.

    1983-01-01

    A recursive, extended Kalman-filter approach is applied to the identifiction of rotor damping levels of representative helicopter dynamic systems. The general formulation of the approach is presented in the context of a typically posed stochastic estimation problem, and the method is analytically applied to determining the damping levels of a coupled rotor-body system. The identified damping covergence characteristics are studied for sensitivity to both constant-coefficient and periodic-coefficient measurement models, process-noise covariance levels, and specified initial estimates of the rotor-system damping. A second application of the method to identifying the plant model for a highly damped, isolated flapping blade with a constant-coefficient state model (hover) and a periodic-coefficient state model (forward flight) is also investigated. The parameter-identification capability is evaluated for the effect of periodicity on the plant model coefficients and the influence of different measurement noise levels.

  14. The dynamic radiation environment assimilation model (DREAM)

    SciTech Connect

    Reeves, Geoffrey D; Koller, Josef; Tokar, Robert L; Chen, Yue; Henderson, Michael G; Friedel, Reiner H

    2010-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate results than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.

  15. Mathematical Models for HIV Transmission Dynamics

    PubMed Central

    Cassels, Susan; Clark, Samuel J.; Morris, Martina

    2012-01-01

    Summary HIV researchers have long appreciated the need to understand the social and behavioral determinants of HIV-related risk behavior, but the cumulative impact of individual behaviors on population-level HIV outcomes can be subtle and counterintuitive, and the methods for studying this are rarely part of a traditional social science or epidemiology training program. Mathematical models provide a way to examine the potential effects of the proximate biologic and behavioral determinants of HIV transmission dynamics, alone and in combination. The purpose of this article is to show how mathematical modeling studies have contributed to our understanding of the dynamics and disparities in the global spread of HIV. Our aims are to demonstrate the value that these analytic tools have for social and behavioral sciences in HIV prevention research, to identify gaps in the current literature, and to suggest directions for future research. PMID:18301132

  16. Dynamical models of hydrogenated amorphous silicon

    NASA Astrophysics Data System (ADS)

    Mousseau, Normand; Lewis, Laurent J.

    1991-04-01

    The results of our molecular-dynamics simulation of bulk hydrogenated amorphous silicon using empirical potentials are presented. More specifically, we discuss a dynamical procedure for incorporating hydrogen into a pure amorphous silicon matrix, which is derived from the concept of floating bonds put forward by Pantelides [Phys. Rev. Lett. 57, 2979 (1986)]. The structures resulting from this model are compared with those obtained with use of a static approach recently developed by us. This method exhibits considerable improvement over the previous one and, in particular, unambiguously reveals the strain-relieving role of hydrogen. While the former model leads to substantial overcoordination, the present one results in almost perfect tetrahedral bonding, with an average coordination number Z=4.03, the lowest value ever achieved using a Stillinger-Weber potential. The simulations are also used to calculate the vibrational densities of states, which are found to be in good accord with corresponding neutron-scattering measurements.

  17. Dynamic plasmapause model based on THEMIS measurements

    NASA Astrophysics Data System (ADS)

    Liu, X.; Liu, W.; Cao, J. B.; Fu, H. S.; Yu, J.; Li, X.

    2015-12-01

    This paper presents a dynamic plasmapause location model established based on 5 years of Time History of Events and Macroscale Interactions during Substorms (THEMIS) measurements from 2009 to 2013. In total, 5878 plasmapause crossing events are identified, sufficiently covering all 24 magnetic local time (MLT) sectors. Based on this plasmapause crossing database, we investigate the correlations between plasmapause locations with solar wind parameters and geomagnetic indices. Input parameters for the best fits are obtained for different MLT sectors, and finally, we choose five input parameters to build a plasmapause location model, including 5 min-averaged SYM-H, AL, and AU indices as well as hourly-averaged AE and Kp indices. two out-of-sample comparisons on the evolution of the plasmapause is shown during two magnetic storms, demonstrating good agreement between model results and observations. Two major advantages are achieved by this model. First, this model provides plasmapause locations at 24 MLT sectors, still providing good consistency with observations. Second, this model is able to reproduce dynamic variations of the plasmapause on timescales as short as 5 min.

  18. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    NASA Astrophysics Data System (ADS)

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multicomponent metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamical aspects of a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulations with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (self diffusion coefficient, self relaxation time, and shear viscosity) bordered at Tx˜1300 K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs well above the melting point of the system (Tm˜900 K) in the equilibrium liquid state; and the crossover temperature Tx is roughly twice of the glass-transition temperature of the system (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a nonparametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter α2 and the four-point correlation function χ4.

  19. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    DOE PAGESBeta

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at Tx ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (Tm ~ 900K), and the crossover temperature ismore » roughly twice of the glass-transition temperature (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

  20. Molecular dynamics modelling of solidification in metals

    SciTech Connect

    Boercker, D.B.; Belak, J.; Glosli, J.

    1997-12-31

    Molecular dynamics modeling is used to study the solidification of metals at high pressure and temperature. Constant pressure MD is applied to a simulation cell initially filled with both solid and molten metal. The solid/liquid interface is tracked as a function of time, and the data are used to estimate growth rates of crystallites at high pressure and temperature in Ta and Mg.

  1. Modeling the dynamics of nonlinear inductor circuits

    NASA Astrophysics Data System (ADS)

    Deane, Jonathan H. B.

    1994-09-01

    The Jiles-Atherton (J-A) model is applied to the problem of describing the dynamics of a nonlinear circuit driven by a square wave voltage source and comprising a linear resistor and capacitor in series with a nonlinear inductor, whose core displays saturation and hysteresis. The presence of hysteresis is shown to increase the order of the circuit by one. Period-multiplication and chaos are observed and excellent agreement is obtained between experiment and simulation.

  2. Dynamic analysis of a parasite population model

    NASA Astrophysics Data System (ADS)

    Sibona, G. J.; Condat, C. A.

    2002-03-01

    We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.

  3. A dynamic model of thundercloud electric fields

    NASA Technical Reports Server (NTRS)

    Nisbet, J. S.

    1983-01-01

    A description is given of the first results obtained with a new type of dynamic electrical model of a thundercloud that allows the charge rearrangement produced in arc breakdown, as well as the conduction and displacement currents, to be calculated with realistic generator configurations. The model demonstrates the great complexity of behavior of thunderclouds owing to the interaction of the nonlinear breakdown mechanisms, the energy stored in the electric field, and a conductivity that varies with altitude. It is also seen that dynamic charge distributions and electric fields are quite different from static distributions. It is noted that these differences affect the initial conditions before and after lightning strokes. The conduction current density to the ionosphere is very much larger in the dynamic cases than in static simulations. Such basic properties of thunderclouds as the production of cloud-to-ground strokes are seen as compatible only with a very limited range of thundercloud models. Another finding is that coronal and convection currents cause the electric fields at the surface to be much smaller than they would be in their absence.

  4. Adaptive dynamics for physiologically structured population models.

    PubMed

    Durinx, Michel; Metz, J A J Hans; Meszéna, Géza

    2008-05-01

    We develop a systematic toolbox for analyzing the adaptive dynamics of multidimensional traits in physiologically structured population models with point equilibria (sensu Dieckmann et al. in Theor. Popul. Biol. 63:309-338, 2003). Firstly, we show how the canonical equation of adaptive dynamics (Dieckmann and Law in J. Math. Biol. 34:579-612, 1996), an approximation for the rate of evolutionary change in characters under directional selection, can be extended so as to apply to general physiologically structured population models with multiple birth states. Secondly, we show that the invasion fitness function (up to and including second order terms, in the distances of the trait vectors to the singularity) for a community of N coexisting types near an evolutionarily singular point has a rational form, which is model-independent in the following sense: the form depends on the strategies of the residents and the invader, and on the second order partial derivatives of the one-resident fitness function at the singular point. This normal form holds for Lotka-Volterra models as well as for physiologically structured population models with multiple birth states, in discrete as well as continuous time and can thus be considered universal for the evolutionary dynamics in the neighbourhood of singular points. Only in the case of one-dimensional trait spaces or when N = 1 can the normal form be reduced to a Taylor polynomial. Lastly we show, in the form of a stylized recipe, how these results can be combined into a systematic approach for the analysis of the (large) class of evolutionary models that satisfy the above restrictions. PMID:17943289

  5. DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT

    SciTech Connect

    Privon, G. C.; Evans, A. S.; Barnes, J. E.; Hibbard, J. E.; Yun, M. S.; Mazzarella, J. M.; Armus, L.; Surace, J.

    2013-07-10

    We present dynamical models of four interacting systems: NGC 5257/8, The Mice, the Antennae, and NGC 2623. The parameter space of the encounters are constrained using the Identikit model-matching and visualization tool. Identikit utilizes hybrid N-body and test particle simulations to enable rapid exploration of the parameter space of galaxy mergers. The Identikit-derived matches of these systems are reproduced with self-consistent collisionless simulations which show very similar results. The models generally reproduce the observed morphology and H I kinematics of the tidal tails in these systems with reasonable properties inferred for the progenitor galaxies. The models presented here are the first to appear in the literature for NGC 5257/8 and NGC 2623, and The Mice and the Antennae are compared with previously published models. Based on the assumed mass model and our derived initial conditions, the models indicate that the four systems are currently being viewed 175-260 Myr after first passage and cover a wide range of merger stages. In some instances there are mismatches between the models and the data (e.g., in the length of a tail); these are likely due to our adoption of a single mass model for all galaxies. Despite the use of a single mass model, these results demonstrate the utility of Identikit in constraining the parameter space for galaxy mergers when applied to real data.

  6. Approaches for modeling magnetic nanoparticle dynamics

    PubMed Central

    Reeves, Daniel B; Weaver, John B

    2014-01-01

    Magnetic nanoparticles are useful biological probes as well as therapeutic agents. There have been several approaches used to model nanoparticle magnetization dynamics for both Brownian as well as Néel rotation. The magnetizations are often of interest and can be compared with experimental results. Here we summarize these approaches including the Stoner-Wohlfarth approach, and stochastic approaches including thermal fluctuations. Non-equilibrium related temperature effects can be described by a distribution function approach (Fokker-Planck equation) or a stochastic differential equation (Langevin equation). Approximate models in several regimes can be derived from these general approaches to simplify implementation. PMID:25271360

  7. A dynamical model for bark beetle outbreaks.

    PubMed

    Křivan, Vlastimil; Lewis, Mark; Bentz, Barbara J; Bewick, Sharon; Lenhart, Suzanne M; Liebhold, Andrew

    2016-10-21

    Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees are highly nonlinear, due to complex aggregation behaviors exhibited by beetles attacking trees. Models have a role to play in helping unravel the effects of variable tree resistance and beetle aggregation on bark beetle outbreaks. In this article we develop a new mathematical model for bark beetle outbreaks using an analogy with epidemiological models. Because the model operates on several distinct time scales, singular perturbation methods are used to simplify the model. The result is a dynamical system that tracks populations of uninfested and infested trees. A limiting case of the model is a discontinuous function of state variables, leading to solutions in the Filippov sense. The model assumes an extensive seed-bank so that tree recruitment is possible even if trees go extinct. Two scenarios are considered for immigration of new beetles. The first is a single tree stand with beetles immigrating from outside while the second considers two forest stands with beetle dispersal between them. For the seed-bank driven recruitment rate, when beetle immigration is low, the forest stand recovers to a beetle-free state. At high beetle immigration rates beetle populations approach an endemic equilibrium state. At intermediate immigration rates, the model predicts bistability as the forest can be in either of the two equilibrium states: a healthy forest, or a forest with an endemic beetle population. The model bistability leads to hysteresis. Interactions between two stands show how a less resistant stand of trees may provide an initial toe-hold for the invasion, which later leads to a regional beetle outbreak in the

  8. Dynamic stall simulation including turbulence modeling

    SciTech Connect

    Allet, A.; Halle, S.; Paraschivoiu, I.

    1995-09-01

    The objective of this study is to investigate the two-dimensional unsteady flow around an airfoil undergoing a Darrieus motion in dynamic stall conditions. For this purpose, a numerical solver based on the solution of the Reynolds-averaged Navier-Stokes equations expressed in a streamfunction-vorticity formulation in a non-inertial frame of reference was developed. The governing equations are solved by the streamline upwind Petrov-Galerkin finite element method (FEM). Temporal discretization is achieved by second-order-accurate finite differences. The resulting global matrix system is linearized by the Newton method and solved by the generalized minimum residual method (GMRES) with an incomplete triangular factorization preconditioning (ILU). Turbulence effects are introduced in the solver by an eddy viscosity model. The investigation centers on an evaluation of the possibilities of several turbulence models, including the algebraic Cebeci-Smith model (CSM) and the nonequilibrium Johnson-King model (JKM). In an effort to predict dynamic stall features on rotating airfoils, first the authors present some testing results concerning the performance of both turbulence models for the flat plate case. Then, computed flow structure together with aerodynamic coefficients for a NACA 0015 airfoil in Darrieus motion under stall conditions are presented.

  9. New concepts for dynamic plant uptake models.

    PubMed

    Rein, A; Legind, C N; Trapp, S

    2011-03-01

    Models for the prediction of chemical uptake into plants are widely applied tools for human and wildlife exposure assessment, pesticide design and for environmental biotechnology such as phytoremediation. Steady-state considerations are often applied, because they are simple and have a small data need. However, often the emission pattern is non-steady. Examples are pesticide spraying, or the application of manure and sewage sludge on agricultural fields. In these scenarios, steady-state solutions are not valid, and dynamic simulation is required. We compared different approaches for dynamic modelling of plant uptake in order to identify relevant processes and timescales of processes in the soil-plant-air system. Based on the outcome, a new model concept for plant uptake models was developed, approximating logistic growth and coupling transpiration to growing plant mass. The underlying system of differential equations was solved analytically for the inhomogenous case, i.e. for constant input. By superposition of the results of n periods, changes in emission and input data between periods are considered. This combination allows to mimic most input functions that are relevant in practice. The model was set up, parameterized and tested for uptake into growing crops. The outcome was compared with a numerical solution, to verify the mathematical structure. PMID:21391147

  10. Restoration of the Potosi Dynamic Model 2010

    SciTech Connect

    Adushita, Yasmin; Leetaru, Hannes

    2014-09-30

    In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate

  11. Dynamical models of happiness with fractional order

    NASA Astrophysics Data System (ADS)

    Song, Lei; Xu, Shiyun; Yang, Jianying

    2010-03-01

    This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.

  12. Transition matrix model for evolutionary game dynamics.

    PubMed

    Ermentrout, G Bard; Griffin, Christopher; Belmonte, Andrew

    2016-03-01

    We study an evolutionary game model based on a transition matrix approach, in which the total change in the proportion of a population playing a given strategy is summed directly over contributions from all other strategies. This general approach combines aspects of the traditional replicator model, such as preserving unpopulated strategies, with mutation-type dynamics, which allow for nonzero switching to unpopulated strategies, in terms of a single transition function. Under certain conditions, this model yields an endemic population playing non-Nash-equilibrium strategies. In addition, a Hopf bifurcation with a limit cycle may occur in the generalized rock-scissors-paper game, unlike the replicator equation. Nonetheless, many of the Folk Theorem results are shown to hold for this model. PMID:27078323

  13. Transition matrix model for evolutionary game dynamics

    NASA Astrophysics Data System (ADS)

    Ermentrout, G. Bard; Griffin, Christopher; Belmonte, Andrew

    2016-03-01

    We study an evolutionary game model based on a transition matrix approach, in which the total change in the proportion of a population playing a given strategy is summed directly over contributions from all other strategies. This general approach combines aspects of the traditional replicator model, such as preserving unpopulated strategies, with mutation-type dynamics, which allow for nonzero switching to unpopulated strategies, in terms of a single transition function. Under certain conditions, this model yields an endemic population playing non-Nash-equilibrium strategies. In addition, a Hopf bifurcation with a limit cycle may occur in the generalized rock-scissors-paper game, unlike the replicator equation. Nonetheless, many of the Folk Theorem results are shown to hold for this model.

  14. AFDM: An Advanced Fluid-Dynamics Model

    SciTech Connect

    Bohl, W.R.; Parker, F.R. ); Wilhelm, D. . Inst. fuer Neutronenphysik und Reaktortechnik); Berthier, J. ); Goutagny, L. . Inst. de Protection et de Surete Nucleaire); Ninokata,

    1990-09-01

    AFDM, or the Advanced Fluid-Dynamics Model, is a computer code that investigates new approaches simulating the multiphase-flow fluid-dynamics aspects of severe accidents in fast reactors. The AFDM formalism starts with differential equations similar to those in the SIMMER-II code. These equations are modified to treat three velocity fields and supplemented with a variety of new models. The AFDM code has 12 topologies describing what material contacts are possible depending on the presence or absence of a given material in a computational cell, on the dominant liquid, and on the continuous phase. Single-phase, bubbly, churn-turbulent, cellular, and dispersed flow regimes are permitted for the pool situations modeled. Virtual mass terms are included for vapor in liquid-continuous flow. Interfacial areas between the continuous and discontinuous phases are convected to allow some tracking of phenomenological histories. Interfacial areas are also modified by models of nucleation, dynamic forces, turbulence, flashing, coalescence, and mass transfer. Heat transfer is generally treated using engineering correlations. Liquid-vapor phase transitions are handled with the nonequilibrium, heat-transfer-limited model, whereas melting and freezing processes are based on equilibrium considerations. Convection is treated using a fractional-step method of time integration, including a semi-implicit pressure iteration. A higher-order differencing option is provided to control numerical diffusion. The Los Alamos SESAME equation-of-state has been implemented using densities and temperatures as the independent variables. AFDM programming has vectorized all computational loops consistent with the objective of producing an exportable code. 24 refs., 4 figs.

  15. An efficient model of drillstring dynamics

    NASA Astrophysics Data System (ADS)

    Butlin, T.; Langley, R. S.

    2015-11-01

    High amplitude vibration regimes can cause significant damage to oilwell drillstrings: torsional stick-slip oscillation, forward whirl and backward whirl are each associated with different kinds of damage. There is a need for models of drillstring dynamics that can predict this variety of phenomena that are: efficient enough to carry out parametric studies; simple enough to provide insight into the underlying physics, and which retain sufficient detail to correlate to real drillstrings. The modelling strategy presented in this paper attempts to balance these requirements. It includes the dynamics of the full length of the drillstring over a wide bandwidth but assumes that the main nonlinear effects are due to spatially localised regions of strong nonlinearity, for example at the drillbit cutting interface and at stabilisers where the borehole wall clearance is smallest. The equations of motion can be formed in terms of this reduced set of degrees of freedom, coupled to the nonlinear contact laws and solved by time-domain integration. Two implementations of this approach are presented, using (1) digital filters and (2) a finite element model to describe the linear dynamics. Choosing a sampling period that is less than the group delay between nonlinear degrees of freedom results in a decoupled set of equations that can be solved very efficiently. Several cases are presented which demonstrate a variety of phenomena, including stick-slip oscillation; forward whirl and backward whirl. Parametric studies are shown which reveal the conditions which lead to high amplitude vibration regimes, and an analytic regime boundary is derived for torsional stick-slip oscillation. The digital filter and finite element models are shown to be in good agreement and are similarly computationally efficient. The digital filter approach has the advantage of more intuitive interpretation, while the finite element model is more readily implemented using existing software packages.

  16. Dynamic geometry, brain function modeling, and consciousness.

    PubMed

    Roy, Sisir; Llinás, Rodolfo

    2008-01-01

    Pellionisz and Llinás proposed, years ago, a geometric interpretation towards understanding brain function. This interpretation assumes that the relation between the brain and the external world is determined by the ability of the central nervous system (CNS) to construct an internal model of the external world using an interactive geometrical relationship between sensory and motor expression. This approach opened new vistas not only in brain research but also in understanding the foundations of geometry itself. The approach named tensor network theory is sufficiently rich to allow specific computational modeling and addressed the issue of prediction, based on Taylor series expansion properties of the system, at the neuronal level, as a basic property of brain function. It was actually proposed that the evolutionary realm is the backbone for the development of an internal functional space that, while being purely representational, can interact successfully with the totally different world of the so-called "external reality". Now if the internal space or functional space is endowed with stochastic metric tensor properties, then there will be a dynamic correspondence between events in the external world and their specification in the internal space. We shall call this dynamic geometry since the minimal time resolution of the brain (10-15 ms), associated with 40 Hz oscillations of neurons and their network dynamics, is considered to be responsible for recognizing external events and generating the concept of simultaneity. The stochastic metric tensor in dynamic geometry can be written as five-dimensional space-time where the fifth dimension is a probability space as well as a metric space. This extra dimension is considered an imbedded degree of freedom. It is worth noticing that the above-mentioned 40 Hz oscillation is present both in awake and dream states where the central difference is the inability of phase resetting in the latter. This framework of dynamic

  17. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

    PubMed

    Ogbunugafor, C Brandon; Robinson, Sean P

    2016-01-01

    Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918

  18. Target fishing of glycopentalone using integrated inverse docking and reverse pharmacophore mapping approach.

    PubMed

    Gurung, A B; Ali, M A; Bhattacharjee, A; Al-Anazi, K M; Farah, M A; Al-Hemaid, F M; Abou-Tarboush, F M; Lee, J; Kim, S Y; Al-Anazi, F S M

    2016-01-01

    Glycopentalone isolated from Glycosmis pentaphylla (family Rutaceae) has cytotoxic and apoptosis inducing effects in various human cancer cell lines; however, its mode of action is not known. Therefore, target fishing of glycopentalone using a combined approach of inverse docking and reverse pharmacophore mapping approach was used to identify potential targets of glycopentalone, and gain insight into its binding modes against the selected molecular targets, viz., CDK-2, CDK-6, Topoisomerase I, Bcl-2, VEGFR-2, Telomere:G-quadruplex and Topoisomerase II. These targets were chosen based on their key roles in the progression of cancer via regulation of cell cycle and DNA replication. Molecular docking analysis revealed that glycopentalone displayed binding energies ranging from -6.38 to -8.35 kcal/mol and inhibition constants ranging from 0.758 to 20.90 μM. Further, the binding affinities of glycopentalone to the targets were in the order: Telomere:G-quadruplex > VEGFR-2 > CDK-6 > CDK-2 > Topoisomerase II > Topoisomerase I > Bcl-2. Binding mode analysis revealed critical hydrogen bonds as well as hydrophobic interactions with the targets. The targets were validated by reverse pharmacophore mapping of glycopentalone against a set of 2241 known human target proteins which revealed CDK-2 and VEGFR-2 as the most favorable targets. The glycopentalone was well mapped to CDK-2 and VEGFR-2 which involve six pharmacophore features (two hydrophobic centers and four hydrogen bond acceptors) and nine pharmacophore features (five hydrophobic, two hydrogen bond acceptors and two hydrogen bond donors), respectively. The present computational approach may aid in rational identification of targets for small molecules against large set of candidate macromolecules before bioassays validation. PMID:27525951

  19. Dynamic Modeling of the SMAP Rotating Flexible Antenna

    NASA Technical Reports Server (NTRS)

    Nayeri, Reza D.

    2012-01-01

    Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications

  20. Dynamic modeling of hydrostatic guideway considering compressibility and inertia effect

    NASA Astrophysics Data System (ADS)

    Du, Yikang; Mao, Kuanmin; Zhu, Yaming; Wang, Fengyun; Mao, Xiaobo; Li, Bin

    2015-03-01

    Hydrostatic guideways are used as an alternative to contact bearings due to high stiffness and high damping in heavy machine tools. To improve the dynamic characteristic of bearing structure, the dynamic modeling of the hydrostatic guidway should be accurately known. This paper presents a "mass-spring-Maxwell" model considering the effects of inertia, squeeze, compressibility and static bearing. To determine the dynamic model coefficients, numerical simulation of different cases between displacement and dynamic force of oil film are performed with fluent code. Simulation results show that hydrostatic guidway can be taken as a linear system when it is subjected to a small oscillation amplitude. Based on a dynamic model and numerical simulation, every dynamic model's parameters are calculated by the Levenberg-Marquardt algorithm. Identification results show that "mass-spring-damper" model is the most appropriate dynamic model of the hydrostatic guidway. This paper provides a reference and preparation for the analysis of the dynamic model of the similar hydrostatic bearings.

  1. A Model of Canine Leukocyte Telomere Dynamics

    PubMed Central

    Benetos, Athanase; Kimura, Masayuki; Labat, Carlos; Buchoff, Gerald M.; Huber, Shell; Labat, Laura; Lu, Xiaobin; Aviv, Abraham

    2011-01-01

    Summary Recent studies have found associations of leukocyte telomere length (TL) with diseases of aging and with longevity. However, it is unknown whether birth leukocyte TL or its age-dependent attrition— the two factors that determine leukocyte TL dynamics— explains these associations, since acquiring this information entails monitoring individuals over their entire life course. We tested in dogs a model of leukocyte TL dynamics, based on the following premises: (i) TL is synchronized among somatic tissues; (ii) TL in skeletal muscle, which is largely post-mitotic, is a measure of TL in early development; (iii) the difference between TL in leukocytes and muscle (ΔLMTL) is the extent of leukocyte TL shortening since early development. Using this model, we observed in 83 dogs (ages 4–42 months) no significant change with age in TLs of skeletal muscle and a shorter TL in leukocytes than in skeletal muscle (P<0.0001). Age explained 43% of the variation in ΔLMTL (P<0.00001) but only 6% of the variation in leukocyte TL (P=0.035) among dogs. Accordingly, muscle TL and ΔLMTL provide the two essential factors of leukocyte TL dynamics in the individual dog. When applied to humans, the partition of the contribution of leukocyte TL during early development versus telomere shortening afterward might provide information about whether the individual’s longevity is calibrated to either one or both factors that define leukocyte TL dynamics. PMID:21917112

  2. Comet Gas and Dust Dynamics Modeling

    NASA Technical Reports Server (NTRS)

    Von Allmen, Paul A.; Lee, Seungwon

    2010-01-01

    This software models the gas and dust dynamics of comet coma (the head region of a comet) in order to support the Microwave Instrument for Rosetta Orbiter (MIRO) project. MIRO will study the evolution of the comet 67P/Churyumov-Gerasimenko's coma system. The instrument will measure surface temperature, gas-production rates and relative abundances, and velocity and excitation temperatures of each species along with their spatial temporal variability. This software will use these measurements to improve the understanding of coma dynamics. The modeling tool solves the equation of motion of a dust particle, the energy balance equation of the dust particle, the continuity equation for the dust and gas flow, and the dust and gas mixture energy equation. By solving these equations numerically, the software calculates the temperature and velocity of gas and dust as a function of time for a given initial gas and dust production rate, and a dust characteristic parameter that measures the ability of a dust particle to adjust its velocity to the local gas velocity. The software is written in a modular manner, thereby allowing the addition of more dynamics equations as needed. All of the numerical algorithms are added in-house and no third-party libraries are used.

  3. Evaluation of novel Akt1 inhibitors as anticancer agents using virtual co-crystallized pharmacophore generation.

    PubMed

    Al-Sha'er, Mahmoud A; Mansi, Iman; Almazari, Inas; Hakooz, Nancy

    2015-11-01

    The pharmacophoric features of the virtual co-crystallized protein of 17 Akt1 proteins were downloaded from the protein data bank, and explored to end up with 132 generated pharmacophores that had been evaluated using the decoy list composed of 1724 compounds. The areas under the curve of the Receiver-Operating Characteristic (ROC-AUC) were sorted, and the highest ranked pharmacophore 3MV5_2_01 was selected to be used as a searching tool in the National Cancer Institute (NCI) database. The captured hits were mapped based on successful hypotheses and the best fitted compounds were selected. The inhibition of Akt1 was measured and expressed as a percentage of inhibition. 24 out of the 40 compounds showed inhibition of Akt1, out of which 13 compounds showed more than 50% inhibition. Compound 1 showed 93.3% inhibition at 100 μM concentration. To confirm the inhibition of Akt1 phosphorylation, MCF10A cell line was co-treated with 12-O-tetradecanoylphorbol-13-acetate (TPA) and 100 μM of each of the most potent 13 Akt inhibitors (1-13). It was found that compounds 1 exert 91.6% inhibition of Akt1 phosphorylation in MCF10A cell line. PMID:26485540

  4. Consequence modeling using the fire dynamics simulator.

    PubMed

    Ryder, Noah L; Sutula, Jason A; Schemel, Christopher F; Hamer, Andrew J; Van Brunt, Vincent

    2004-11-11

    The use of Computational Fluid Dynamics (CFD) and in particular Large Eddy Simulation (LES) codes to model fires provides an efficient tool for the prediction of large-scale effects that include plume characteristics, combustion product dispersion, and heat effects to adjacent objects. This paper illustrates the strengths of the Fire Dynamics Simulator (FDS), an LES code developed by the National Institute of Standards and Technology (NIST), through several small and large-scale validation runs and process safety applications. The paper presents two fire experiments--a small room fire and a large (15 m diameter) pool fire. The model results are compared to experimental data and demonstrate good agreement between the models and data. The validation work is then extended to demonstrate applicability to process safety concerns by detailing a model of a tank farm fire and a model of the ignition of a gaseous fuel in a confined space. In this simulation, a room was filled with propane, given time to disperse, and was then ignited. The model yields accurate results of the dispersion of the gas throughout the space. This information can be used to determine flammability and explosive limits in a space and can be used in subsequent models to determine the pressure and temperature waves that would result from an explosion. The model dispersion results were compared to an experiment performed by Factory Mutual. Using the above examples, this paper will demonstrate that FDS is ideally suited to build realistic models of process geometries in which large scale explosion and fire failure risks can be evaluated with several distinct advantages over more traditional CFD codes. Namely transient solutions to fire and explosion growth can be produced with less sophisticated hardware (lower cost) than needed for traditional CFD codes (PC type computer verses UNIX workstation) and can be solved for longer time histories (on the order of hundreds of seconds of computed time) with

  5. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems

    PubMed Central

    2016-01-01

    Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of “ODEs and formalized flow diagrams” as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler’s behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918

  6. Models of the Dynamic Deformations of Polymers

    NASA Astrophysics Data System (ADS)

    Merzhievsky, Lev; Voronin, Mihail; Korchagina, Anna

    2013-06-01

    In the process of deformation under the influence of external loading polymeric mediums show the complicated behavior connected with features of their structure. For amorphous polymers distinguish three physical conditions - glasslike, highlyelastic and viscoplastic. To each of the listed conditions there corresponds to mikro - meso- and macrostructural mechanisms of irreversible deformation. In the report the review of results of construction of models for the description of dynamic and shock-wave deformation of the polymers which are based on developed authors representations about mechanisms of irreversible deformation is made. Models include the formulation of the equations of conservation laws, considering effect of a relaxation of shear stresses in the process of deformation. For closing of models the equations of states with nonspherical tensor of deformations and relation for time of a relaxation of shear stresses are constructed. With using of the formulated models a number of problems of dynamic and shock wave deformations has been solved. The results are compared with corresponding experimental date. Development of the used approach are in summary discussed. To taking into account memory and fractal properties of real polymers is supposed of derivatives and integrals of a fractional order to use. Examples of constitutive equations with derivatives of a fractional order are presented. This work is supported by the Integration project of the Siberian Branch of the Russian Academy of Science 64 and grant RFBR 12-01-00726.

  7. The Dynamical Sine-Gordon Model

    NASA Astrophysics Data System (ADS)

    Hairer, Martin; Shen, Hao

    2016-02-01

    We introduce the dynamical sine-Gordon equation in two space dimensions with parameter {β}, which is the natural dynamic associated to the usual quantum sine-Gordon model. It is shown that when {β2 in (0, 16π/3)} the Wick renormalised equation is well-posed. In the regime {β2 in (0, 4π)}, the Da Prato-Debussche method [J Funct Anal 196(1):180-210, 2002; Ann Probab 31(4):1900-1916, 2003] applies, while for {β2 in [4π, 16π/3)}, the solution theory is provided via the theory of regularity structures [Hairer, Invent Math 198(2):269-504, 2014]. We also show that this model arises naturally from a class of {2 + 1} -dimensional equilibrium interface fluctuation models with periodic nonlinearities. The main mathematical difficulty arises in the construction of the model for the associated regularity structure where the role of the noise is played by a non-Gaussian random distribution similar to the complex multiplicative Gaussian chaos recently analysed in Lacoin et al. [Commun Math Phys 337(2):569-632, 2015].

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

    PubMed

    Sharma, Mukesh C

    2016-06-01

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

  9. Stochastic dynamic models and Chebyshev splines

    PubMed Central

    Fan, Ruzong; Zhu, Bin; Wang, Yuedong

    2015-01-01

    In this article, we establish a connection between a stochastic dynamic model (SDM) driven by a linear stochastic differential equation (SDE) and a Chebyshev spline, which enables researchers to borrow strength across fields both theoretically and numerically. We construct a differential operator for the penalty function and develop a reproducing kernel Hilbert space (RKHS) induced by the SDM and the Chebyshev spline. The general form of the linear SDE allows us to extend the well-known connection between an integrated Brownian motion and a polynomial spline to a connection between more complex diffusion processes and Chebyshev splines. One interesting special case is connection between an integrated Ornstein–Uhlenbeck process and an exponential spline. We use two real data sets to illustrate the integrated Ornstein–Uhlenbeck process model and exponential spline model and show their estimates are almost identical. PMID:26045632

  10. Model-Free Dual Heuristic Dynamic Programming.

    PubMed

    Ni, Zhen; He, Haibo; Zhong, Xiangnan; Prokhorov, Danil V

    2015-08-01

    Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires offline training for the model network, and thus resulting in extra computational cost. In this brief, we propose a model-free DHP (MF-DHP) design based on finite-difference technique. In particular, we adopt multilayer perceptron with one hidden layer for both the action and the critic networks design, and use delayed objective functions to train both the action and the critic networks online over time. We test both the MF-DHP and MB-DHP approaches with a discrete time example and a continuous time example under the same parameter settings. Our simulation results demonstrate that the MF-DHP approach can obtain a control performance competitive with that of the traditional MB-DHP approach while requiring less computational resources. PMID:25955997

  11. Dynamic survival models with spatial frailty.

    PubMed

    Bastos, Leonardo Soares; Gamerman, Dani

    2006-12-01

    In many survival studies, covariates effects are time-varying and there is presence of spatial effects. Dynamic models can be used to cope with the variations of the effects and spatial components are introduced to handle spatial variation. This paper proposes a methodology to simultaneously introduce these components into the model. A number of specifications for the spatial components are considered. Estimation is performed via a Bayesian approach through Markov chain Monte Carlo methods. Models are compared to assess relevance of their components. Analysis of a real data set is performed, showing the relevance of both time-varying covariate effects and spatial components. Extensions to the methodology are proposed along with concluding remarks. PMID:17031498

  12. Simulating aggregate dynamics in ocean biogeochemical models

    NASA Astrophysics Data System (ADS)

    Jackson, George A.; Burd, Adrian B.

    2015-04-01

    The dynamics of elements in the water column is complex, depending on multiple biological and physical processes operating at very different physical scales. Coagulation of particulate material is important for transforming particles and moving them in the water column. Mechanistic models of coagulation processes provide a means to predict these processes, help interpret observations, and provide insight into the processes occurring. However, most model applications have focused on describing simple marine systems and mechanisms. We argue that further model development, in close collaboration with field and experimental scientists, is required in order to extend the models to describe the large-scale elemental distributions and interactions being studied as part of GEOTRACES. Models that provide a fundamental description of trace element-particle interactions are required as are experimental tests of the mechanisms involved and the predictions arising from models. However, a comparison between simple and complicated models of aggregation and trace metal provides a means for understanding the implications of simplifying assumptions and providing guidance as to which simplifications are needed.

  13. Flight Dynamic Model Exchange using XML

    NASA Technical Reports Server (NTRS)

    Jackson, E. Bruce; Hildreth, Bruce L.

    2002-01-01

    The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.

  14. Dynamical Vertex Approximation for the Hubbard Model

    NASA Astrophysics Data System (ADS)

    Toschi, Alessandro

    A full understanding of correlated electron systems in the physically relevant situations of three and two dimensions represents a challenge for the contemporary condensed matter theory. However, in the last years considerable progress has been achieved by means of increasingly more powerful quantum many-body algorithms, applied to the basic model for correlated electrons, the Hubbard Hamiltonian. Here, I will review the physics emerging from studies performed with the dynamical vertex approximation, which includes diagrammatic corrections to the local description of the dynamical mean field theory (DMFT). In particular, I will first discuss the phase diagram in three dimensions with a special focus on the commensurate and incommensurate magnetic phases, their (quantum) critical properties, and the impact of fluctuations on electronic lifetimes and spectral functions. In two dimensions, the effects of non-local fluctuations beyond DMFT grow enormously, determining the appearance of a low-temperature insulating behavior for all values of the interaction in the unfrustrated model: Here the prototypical features of the Mott-Hubbard metal-insulator transition, as well as the existence of magnetically ordered phases, are completely overwhelmed by antiferromagnetic fluctuations of exponentially large extension, in accordance with the Mermin-Wagner theorem. Eventually, by a fluctuation diagnostics analysis of cluster DMFT self-energies, the same magnetic fluctuations are identified as responsible for the pseudogap regime in the holed-doped frustrated case, with important implications for the theoretical modeling of the cuprate physics.

  15. Modeling of dynamic bipolar plasma sheaths

    NASA Astrophysics Data System (ADS)

    Grossmann, J. M.; Swanekamp, S. B.; Ottinger, P. F.

    1992-01-01

    The behavior of a one-dimensional plasma sheath is described in regimes where the sheath is not in equilibrium because it carries current densities that are either time dependent, or larger than the bipolar Child-Langmuir level determined from the injected ion flux. Earlier models of dynamic bipolar sheaths assumed that ions and electrons evolve in a series of quasiequilibria. In addition, sheath growth was described by the equation Zen0ẋs=‖ ji‖-Zen0u0, where ẋs is the velocity of the sheath edge, ji is the ion current density, n0u0 is the injected ion flux density, and Ze is the ion charge. In this paper, a generalization of the bipolar electron-to-ion current density ratio formula is derived to study regimes where ions are not in equilibrium. A generalization of the above sheath growth equation is also developed, which is consistent with the ion continuity equation and which reveals new physics of sheath behavior associated with the emitted electrons and their evolution. Based on these findings, two new models of dynamic bipolar sheaths are developed. Larger sheath sizes and potentials than those of earlier models are found. In certain regimes, explosive sheath growth is predicted.

  16. Dynamic displays of chemical process flowsheet models

    SciTech Connect

    Aull, J.E.

    1996-11-01

    This paper describes the algorithms used in constructing dynamic graphical displays of a process flowsheet. Movies are created which portray changes in the process over time using animation in the flowsheet such as individual streams that take on a color keyed to the current flow rate, tank levels that visibly rise and fall and {open_quotes}gauges{close_quotes} that move to display parameter values. Movies of this type can be a valuable tool for visualizing, analyzing, and communicating the behavior of a process model. This paper describes the algorithms used in constructing displays of this kind for dynamic models using the SPEEDUP{trademark} modeling package and the GMS{trademark} graphics package. It also tells how data is exported from the SPEEDUP{trademark} package to GMS{trademark} and describes how a user environment for running movies and editing flowsheets is set up. The algorithms are general enough to be applied to other processes and graphics packages. In fact the techniques described here can be used to create movies of any time-dependent data.

  17. Numerical modeling of bubble dynamics in magmas

    NASA Astrophysics Data System (ADS)

    Huber, Christian; Su, Yanqing; Parmigiani, Andrea

    2014-05-01

    Understanding the complex non-linear physics that governs volcanic eruptions is contingent on our ability to characterize the dynamics of bubbles and its effect on the ascending magma. The exsolution and migration of bubbles has also a great impact on the heat and mass transport in and out of magma bodies stored at shallow depths in the crust. Multiphase systems like magmas are by definition heterogeneous at small scales. Although mixture theory or homogenization methods are convenient to represent multiphase systems as a homogeneous equivalent media, these approaches do not inform us on possible feedbacks at the pore-scale and can be significantly misleading. In this presentation, we discuss the development and application of bubble-scale multiphase flow modeling to address the following questions : How do bubbles impact heat and mass transport in magma chambers ? How efficient are chemical exchanges between the melt and bubbles during magma decompression? What is the role of hydrodynamic interactions on the deformation of bubbles while the magma is sheared? Addressing these questions requires powerful numerical methods that accurately model the balance between viscous, capillary and pressure stresses. We discuss how these bubble-scale models can provide important constraints on the dynamics of magmas stored at shallow depth or ascending to the surface during an eruption.

  18. Mathematical modeling of infectious disease dynamics

    PubMed Central

    Siettos, Constantinos I.; Russo, Lucia

    2013-01-01

    Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host–pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works. PMID:23552814

  19. Aerodynamics modeling of towed-cable dynamics

    SciTech Connect

    Kang, S.W.; Latorre, V.R.

    1991-01-17

    The dynamics of a cable/drogue system being towed by an orbiting aircraft has been investigated as a part of an LTWA project for the Naval Air Systems Command. We present here a status report on the tasks performed under Phase 1. We have accomplished the following tasks under Phase 1: A literature survey on the towed-cable motion problem has been conducted. While both static (steady-state) and dynamic (transient) analyses exist in the literature, no single, comprehensive analysis exists that directly addresses the present problem. However, the survey also reveals that, when judiciously applied, these past analyses can serve as useful building blocks for approaching the present problem. A numerical model that addresses several aspects of the towed-cable dynamic problem has been adapted from a Canadian underwater code for the present aerodynamic situation. This modified code, called TOWDYN, analyzes the effects of gravity, tension, aerodynamic drag, and wind. Preliminary results from this code demonstrate that the wind effects alone CAN generate the drogue oscillation behavior, i.e., the yo-yo'' phenomenon. This code also will serve as a benchmark code for checking the accuracy of a more general and complete R D'' model code. We have initiated efforts to develop a general R D model supercomputer code that also takes into account other physical factors, such as induced oscillations and bending stiffness. This general code will be able to evaluate the relative impacts of the various physical parameters, which may become important under certain conditions. This R D code will also enable development of a simpler operational code that can be used by the Naval Air personnel in the field.

  20. Computational fluid dynamics modelling in cardiovascular medicine

    PubMed Central

    Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

    2016-01-01

    This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019

  1. Computational fluid dynamics modelling in cardiovascular medicine.

    PubMed

    Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

    2016-01-01

    This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019

  2. Modeling coupled avulsion and earthquake timescale dynamics

    NASA Astrophysics Data System (ADS)

    Reitz, M. D.; Steckler, M. S.; Paola, C.; Seeber, L.

    2014-12-01

    River avulsions and earthquakes can be hazardous events, and many researchers work to better understand and predict their timescales. Improvements in the understanding of the intrinsic processes of deposition and strain accumulation that lead to these events have resulted in better constraints on the timescales of each process individually. There are however several mechanisms by which these two systems may plausibly become linked. River deposition and avulsion can affect the stress on underlying faults through differential loading by sediment or water. Conversely, earthquakes can affect river avulsion patterns through altering the topography. These interactions may alter the event recurrence timescales, but this dynamic has not yet been explored. We present results of a simple numerical model, in which two systems have intrinsic rates of approach to failure thresholds, but the state of one system contributes to the other's approach to failure through coupling functions. The model is first explored for the simplest case of two linear approaches to failure, and linearly proportional coupling terms. Intriguing coupling dynamics emerge: the system settles into cycles of repeating earthquake and avulsion timescales, which are approached at an exponential decay rate that depends on the coupling terms. The ratio of the number of events of each type and the timescale values also depend on the coupling coefficients and the threshold values. We then adapt the model to a more complex and realistic scenario, in which a river avulses between either side of a fault, with parameters corresponding to the Brahmaputra River / Dauki fault system in Bangladesh. Here the tectonic activity alters the topography by gradually subsiding during the interseismic time, and abruptly increasing during an earthquake. The river strengthens the fault by sediment loading when in one path, and weakens it when in the other. We show this coupling can significantly affect earthquake and avulsion

  3. Modeling the dynamical systems on experimental data

    SciTech Connect

    Janson, N.B.; Anishchenko, V.S.

    1996-06-01

    An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog{close_quote}s heart, a human{close_quote}s heart and a blood circulation system of a white rat. Sampled one-dimensional realizations of these systems were taken as the initial data. Correlation dimensions were calculated to evaluate the embedding dimensions of the systems{close_quote} attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation. {copyright} {ital 1996 American Institute of Physics.}

  4. Dynamic Compaction Modeling of Porous Silica Powder

    NASA Astrophysics Data System (ADS)

    Borg, John P.; Schwalbe, Larry; Cogar, John; Chapman, D. J.; Tsembelis, K.; Ward, Aaron; Lloyd, Andrew

    2006-07-01

    A computational analysis of the dynamic compaction of porous silica is presented and compared with experimental measurements. The experiments were conducted at Cambridge University's one-dimensional flyer plate facility. The experiments shock loaded samples of silica dust of various initial porous densities up to a pressure of 2.25 GPa. The computational simulations utilized a linear Us-Up Hugoniot. The compaction events were modeled with CTH, a 3D Eulerian hydrocode developed at Sandia National Laboratory. Simulated pressures at two test locations are presented and compared with measurements.

  5. Scalar model for frictional precursors dynamics.

    PubMed

    Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano

    2015-01-01

    Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective. PMID:25640079

  6. Unsteady aerodynamics modeling for flight dynamics application

    NASA Astrophysics Data System (ADS)

    Wang, Qing; He, Kai-Feng; Qian, Wei-Qi; Zhang, Tian-Jiao; Cheng, Yan-Qing; Wu, Kai-Yuan

    2012-02-01

    In view of engineering application, it is practicable to decompose the aerodynamics into three components: the static aerodynamics, the aerodynamic increment due to steady rotations, and the aerodynamic increment due to unsteady separated and vortical flow. The first and the second components can be presented in conventional forms, while the third is described using a one-order differential equation and a radial-basis-function (RBF) network. For an aircraft configuration, the mathematical models of 6-component aerodynamic coefficients are set up from the wind tunnel test data of pitch, yaw, roll, and coupled yawroll large-amplitude oscillations. The flight dynamics of an aircraft is studied by the bifurcation analysis technique in the case of quasi-steady aerodynamics and unsteady aerodynamics, respectively. The results show that: (1) unsteady aerodynamics has no effect upon the existence of trim points, but affects their stability; (2) unsteady aerodynamics has great effects upon the existence, stability, and amplitudes of periodic solutions; and (3) unsteady aerodynamics changes the stable regions of trim points obviously. Furthermore, the dynamic responses of the aircraft to elevator deflections are inspected. It is shown that the unsteady aerodynamics is beneficial to dynamic stability for the present aircraft. Finally, the effects of unsteady aerodynamics on the post-stall maneuverability are analyzed by numerical simulation.

  7. Scalar model for frictional precursors dynamics

    PubMed Central

    Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano

    2015-01-01

    Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective. PMID:25640079

  8. Computational social dynamic modeling of group recruitment.

    SciTech Connect

    Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.

    2004-01-01

    The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.

  9. A dynamic localization model with stochastic backscatter

    NASA Astrophysics Data System (ADS)

    Carati, Daniele; Ghosal, Sandip

    1994-12-01

    The modeling of subgrid scales in large-eddy simulation (LES) has been rationalized by the introduction of the dynamic localization procedure. This method allows one to compute rather than prescribe the unknown coefficients in the subgrid-scale model. Formally, the LES equations are supposed to be obtained by applying to the Navier-Stokes equations a 'grid filter' operation. Though the subgrid stress itself is unknown, an identity between subgrid stresses generated by different filters has been derived. Although preliminary tests of the Dynamic Localization Model (DLM) with k-equation have been satisfactory, the use of a negative eddy viscosity to describe backscatter is probably a crude representation of the physics of reverse transfer of energy. Indeed, the model is fully deterministic. Knowing the filtered velocity field and the subgrid-scale energy, the subgrid stress is automatically determined. We know that the LES equations cannot be fully deterministic since the small scales are not resolved. This stems from an important distinction between equilibrium hydrodynamics and turbulence. In equilibrium hydrodynamics, the molecular motions are also not resolved. However, there is a clear separation of scale between these unresolved motions and the relevant hydrodynamic scales. The result of molecular motions can then be separated into an average effect (the molecular viscosity) and some fluctuations. Due to the large number of molecules present in a box with size of the order of the hydrodynamic scale, the ratio between fluctuations and the average effect should be very small (as a result of the 'law of large numbers'). For that reason, the hydrodynamic balance equations are usually purely deterministic. In turbulence, however, there is no clear separation of scale between small and large eddies. In that case, the fluctuations around a deterministic eddy viscosity term could be significant. An eddy noise would then appear through a stochastic term in the subgrid

  10. Modelling of snow avalanche dynamics: influence of model parameters

    NASA Astrophysics Data System (ADS)

    Bozhinskiy, A. N.

    The three-parameter hydraulic model of snow avalanche dynamics including the coefficients of dry and turbulent friction and the coefficient of new-snow-mass entrainment was investigated. The 'Domestic' avalanche site in Elbrus region, Caucasus, Russia, was chosen as the model avalanche range. According to the model, the fixed avalanche run-out can be achieved with various combinations of model parameters. At the fixed value of the coefficient of entrainment me, we have a curve on a plane of the coefficients of dry and turbulent friction. It was found that the family of curves (me is a parameter) are crossed at the single point. The value of the coefficient of turbulent friction at the cross-point remained practically constant for the maximum and average avalanche run-outs. The conclusions obtained are confirmed by the results of modelling for six arbitrarily chosen avalanche sites: three in the Khibiny mountains, Kola Peninsula, Russia, two in the Elbrus region and one idealized site with an exponential longitudinal profile. The dependences of run-out on the coefficient of dry friction are constructed for all the investigated avalanche sites. The results are important for the statistical simulation of avalanche dynamics since they suggest the possibility of using only one random model parameter, namely, the coefficient of dry friction, in the model. The histograms and distribution functions of the coefficient of dry friction are constructed and presented for avalanche sites Nos 22 and 43 (Khibiny mountains) and 'Domestic', with the available series of field data.

  11. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    SciTech Connect

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at Tx ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (Tm ~ 900K), and the crossover temperature is roughly twice of the glass-transition temperature (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.

  12. Driven dynamics of simplified tribological models

    NASA Astrophysics Data System (ADS)

    Vanossi, A.; Braun, O. M.

    2007-08-01

    Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena.

  13. Microscopic model for ultrafast remagnetization dynamics.

    PubMed

    Chimata, Raghuveer; Bergman, Anders; Bergqvist, Lars; Sanyal, Biplab; Eriksson, Olle

    2012-10-12

    In this Letter, we provide a microscopic model for the ultrafast remagnetization of atomic moments already quenched above the Stoner-Curie temperature by a strong laser fluence. Combining first-principles density functional theory, atomistic spin dynamics utilizing the Landau-Lifshitz-Gilbert equation, and a three-temperature model, we analyze the temporal evolution of atomic moments as well as the macroscopic magnetization of bcc Fe and hcp Co covering a broad time scale, ranging from femtoseconds to picoseconds. Our simulations show a variety of complex temporal behavior of the magnetic properties resulting from an interplay between electron, spin, and lattice subsystems, which causes an intricate time evolution of the atomic moment, where longitudinal and transversal fluctuations result in a macrospin moment that evolves highly nonmonotonically. PMID:23102359

  14. A Simple General Model of Evolutionary Dynamics

    NASA Astrophysics Data System (ADS)

    Thurner, Stefan

    Evolution is a process in which some variations that emerge within a population (of, e.g., biological species or industrial goods) get selected, survive, and proliferate, whereas others vanish. Survival probability, proliferation, or production rates are associated with the "fitness" of a particular variation. We argue that the notion of fitness is an a posteriori concept in the sense that one can assign higher fitness to species or goods that survive but one can generally not derive or predict fitness per se. Whereas proliferation rates can be measured, fitness landscapes, that is, the inter-dependence of proliferation rates, cannot. For this reason we think that in a physical theory of evolution such notions should be avoided. Here we review a recent quantitative formulation of evolutionary dynamics that provides a framework for the co-evolution of species and their fitness landscapes (Thurner et al., 2010, Physica A 389, 747; Thurner et al., 2010, New J. Phys. 12, 075029; Klimek et al., 2009, Phys. Rev. E 82, 011901 (2010). The corresponding model leads to a generic evolutionary dynamics characterized by phases of relative stability in terms of diversity, followed by phases of massive restructuring. These dynamical modes can be interpreted as punctuated equilibria in biology, or Schumpeterian business cycles (Schumpeter, 1939, Business Cycles, McGraw-Hill, London) in economics. We show that phase transitions that separate phases of high and low diversity can be approximated surprisingly well by mean-field methods. We demonstrate that the mathematical framework is suited to understand systemic properties of evolutionary systems, such as their proneness to collapse, or their potential for diversification. The framework suggests that evolutionary processes are naturally linked to self-organized criticality and to properties of production matrices, such as their eigenvalue spectra. Even though the model is phrased in general terms it is also practical in the sense

  15. Dynamic causal models and autopoietic systems.

    PubMed

    David, Olivier

    2007-01-01

    Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681

  16. Dynamic Models for Templated Viral Capsid Assembly

    NASA Astrophysics Data System (ADS)

    Hagan, Michael

    2008-03-01

    The replication of many viruses with single-stranded genomes requires the simultaneous assembly of an ordered protein shell, or capsid, and encapsidation of the genome. In this talk, I will present coarse-grained computational and theoretical models that describe the assembly of viral capsid proteins around interior cores, such as polymers and rigid spheres. These models are motivated by two recently developed experimental model systems in which viral proteins dynamically encapsidate inorganic nanoparticles and polyelectrolytes. Model predictions suggest that some forms of cooperative interactions between subunits and cores can dramatically enhance rates and robustness of assembly, as compared to the spontaneous assembly of subunits into empty capsids. For large core-subunit interactions, subunits adsorb onto a core en masse in a disordered manner, and then undergo a cooperative rearrangement into an ordered capsid structure. These assembly pathways are unlike any seen for empty capsids formation. While model predictions suggest that cooperative interactions between disparate assembling components can overcome some limitations of spontaneous assembly, the complexity of multicomponent assembly introduces new forms of kinetic traps that can frustrate assembly, and hence introduces new limitations. These findings have implications for a mechanism in which viruses use interactions between proteins and genomic molecules to promote and control assembly, and thereby control the replication process.

  17. Dynamic Elasticity Model of Resilin Biopolymers

    NASA Astrophysics Data System (ADS)

    Hu, Xiao; Duki, Solomon

    2013-03-01

    Resilin proteins are `super elastic rubbers' in the flight and jumping systems of most insects, and can extend and retract millions of times. Natural resilin exhibits high resilience (> 95%) under high-frequency conditions, and could be stretched to over 300% of its original length with a low elastic modulus of 0.1-3 MPa. However, insight into the underlying molecular mechanisms responsible for resilin elasticity remains undefined. We report on the dynamic structure transitions and functions of full length resilin from fruit fly (D. melanogaster CG15920) and its different functional domains. A dynamic computational model is proposed to explain the super elasticity and energy conversion mechanisms of resilin, providing important insight into structure-function relationships for resilins, as well as other elastomeric proteins. A strong beta-turn transition was experimentally identified in the full length resilin and its non-elastic domains (Exon III). Changes in periodic long-range order were demonstrated during this transition, induced either by thermal or mechanical inputs, to confirm the universality of proposed mechanism. Further, this model offers new options for designing protein-based biopolymers with tunable material applications.

  18. Modeling quantum fluid dynamics at nonzero temperatures

    PubMed Central

    Berloff, Natalia G.; Brachet, Marc; Proukakis, Nick P.

    2014-01-01

    The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluid model is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures. PMID:24704874

  19. Microscopic to Macroscopic Dynamical Models of Sociality

    NASA Astrophysics Data System (ADS)

    Solis Salas, Citlali; Woolley, Thomas; Pearce, Eiluned; Dunbar, Robin; Maini, Philip; Social; Evolutionary Neuroscience Research Group (Senrg) Collaboration

    To help them survive, social animals, such as humans, need to share knowledge and responsibilities with other members of the species. The larger their social network, the bigger the pool of knowledge available to them. Since time is a limited resource, a way of optimising its use is meeting amongst individuals whilst fulfilling other necessities. In this sense it is useful to know how many, and how often, early humans could meet during a given period of time whilst performing other necessary tasks, such as food gathering. Using a simplified model of these dynamics, which comprehend encounter and memory, we aim at producing a lower-bound to the number of meetings hunter-gatherers could have during a year. We compare the stochastic agent-based model to its mean-field approximation and explore some of the features necessary for the difference between low population dynamics and its continuum limit. We observe an emergent property that could have an inference in the layered structure seen in each person's social organisation. This could give some insight into hunter-gatherer's lives and the development of the social layered structure we have today. With support from the Mexican Council for Science and Technology (CONACyT), the Public Education Secretariat (SEP), and the Mexican National Autonomous University's Foundation (Fundacion UNAM).

  20. Modeling Insurgent Network Structure and Dynamics

    NASA Astrophysics Data System (ADS)

    Gabbay, Michael; Thirkill-Mackelprang, Ashley

    2010-03-01

    We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.

  1. Modeling habitat dynamics accounting for possible misclassification

    USGS Publications Warehouse

    Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

    2012-01-01

    Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

  2. Dynamic models of lateritic bauxite formation

    NASA Astrophysics Data System (ADS)

    Zhukov, V. V.; Bogatyrev, B. A.

    2012-09-01

    2D dynamic models of bauxite formation in the weathering mantle covering denudation areas drained by river systems are discussed. The role of relief-forming factors (tectonic uplift, river erosion and denudation of drainage divides), the interrelation of hydrogeological and lithologic structure of the bauxitebearing weathering mantle, and the dynamics of zoning formation above and below groundwater level are described in the models. Creative and destructive epochs of lateritic bauxite formation differing in tectonic regime are distinguished. During the creative epochs, lateritic weathering develops against a background of decreasing denudation and an increase in areas of bauxite formation. The destructive epochs are characterized by intense denudation, cutting down the areas of lateritic bauxite formation and eventually leading to the complete removal of the weathering mantle. Different morphogenetic types and varieties of bauxite-bearing weathering mantles develop during creative and destructive epochs. The morphology of the weathering mantle sections at the deposits of Cenozoic lateritic bauxite in the present-day tropical zone of the Earth corresponds to the destructive epoch, which is characterized by declining areas of lateritic bauxite formation and will end with complete denudation of lateritic bauxite.

  3. Multi-Scale Modeling of Magnetospheric Dynamics

    NASA Technical Reports Server (NTRS)

    Kuznetsova, M. M.; Hesse, M.; Toth, G.

    2012-01-01

    Magnetic reconnection is a key element in many phenomena in space plasma, e.g. Coronal mass Ejections, Magnetosphere substorms. One of the major challenges in modeling the dynamics of large-scale systems involving magnetic reconnection is to quantifY the interaction between global evolution of the magnetosphere and microphysical kinetic processes in diffusion regions near reconnection sites. Recent advances in small-scale kinetic modeling of magnetic reconnection significantly improved our understanding of physical mechanisms controlling the dissipation in the vicinity of the reconnection site in collisionless plasma. However the progress in studies of small-scale geometries was not very helpful for large scale simulations. Global magnetosphere simulations usually include non-ideal processes in terms of numerical dissipation and/or ad hoc anomalous resistivity. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term 11 J did not produce fast reconnection rates observed in kinetic simulations. In collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is nongyrotropic pressure effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and replace ad hoc parameters such as "critical current density" and "anomalous resistivity" with a physically motivated model of dissipation. The primary mechanism controlling the dissipation in the vicinity of the reconnection site in incorporated into MHD description in terms of non-gyrotropic corrections to the induction equation. We will demonstrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution. Our approach allowed for the first time to model loading/unloading cycle in response to steady southward IMF driving. The role of solar wind parameters and

  4. Molecular switch for CLC-K Cl- channel block/activation: optimal pharmacophoric requirements towards high-affinity ligands.

    PubMed

    Liantonio, Antonella; Picollo, Alessandra; Carbonara, Giuseppe; Fracchiolla, Giuseppe; Tortorella, Paolo; Loiodice, Fulvio; Laghezza, Antonio; Babini, Elena; Zifarelli, Giovanni; Pusch, Michael; Camerino, Diana Conte

    2008-01-29

    ClC-Ka and ClC-Kb Cl(-) channels are pivotal for renal salt reabsorption and water balance. There is growing interest in identifying ligands that allow pharmacological interventions aimed to modulate their activity. Starting from available ligands, we followed a rational chemical strategy, accompanied by computational modeling and electrophysiological techniques, to identify the molecular requisites for binding to a blocking or to an activating binding site on ClC-Ka. The major molecular determinant that distinguishes activators from blockers is the level of planarity of the aromatic portions of the molecules: only molecules with perfectly coplanar aromatic groups display potentiating activity. Combining several molecular features of various CLC-K ligands, we discovered that phenyl-benzofuran carboxylic acid derivatives yield the most potent ClC-Ka inhibitors so far described (affinity <10 microM). The increase in affinity compared with 3-phenyl-2-p-chlorophenoxy-propionic acid (3-phenyl-CPP) stems primarily from the conformational constraint provided by the phenyl-benzofuran ring. Several other key structural elements for high blocking potency were identified through a detailed structure-activity relationship study. Surprisingly, some benzofuran-based drugs inhibit ClC-Kb with a similar affinity of <10 microM, thus representing the first inhibitors for this CLC-K isoform identified so far. Based on our data, we established a pharmacophore model that will be useful for the development of drugs targeting CLC-K channels. PMID:18216243

  5. Dynamic thermodiffusion model for binary liquid mixtures.

    PubMed

    Eslamian, Morteza; Saghir, M Ziad

    2009-07-01

    Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring's reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models. PMID:19658691

  6. Dynamic thermodiffusion model for binary liquid mixtures

    NASA Astrophysics Data System (ADS)

    Eslamian, Morteza; Saghir, M. Ziad

    2009-07-01

    Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring’s reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, The Theory of Rate Processes: The Kinetics of Chemical Reactions, Viscosity, Diffusion and Electrochemical Phenomena (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models.

  7. Dynamic hysteresis modeling including skin effect using diffusion equation model

    NASA Astrophysics Data System (ADS)

    Hamada, Souad; Louai, Fatima Zohra; Nait-Said, Nasreddine; Benabou, Abdelkader

    2016-07-01

    An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.

  8. Computational modeling of intraocular gas dynamics.

    PubMed

    Noohi, P; Abdekhodaie, M J; Cheng, Y L

    2015-01-01

    The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency. PMID:26682529

  9. Computational modeling of intraocular gas dynamics

    NASA Astrophysics Data System (ADS)

    Noohi, P.; Abdekhodaie, M. J.; Cheng, Y. L.

    2015-12-01

    The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency.

  10. A dynamical model for mirror movements

    NASA Astrophysics Data System (ADS)

    Daffertshofer, A.; van den Berg, C.; Beek, P. J.

    1999-07-01

    In an experiment involving the unimanual performance of rhythmic movements about the elbow joint, mirror movements (MM) (i.e., unintended, associated movements) were observed in the arm not instructed to move. The amplitude of these movements was small relative to that of the intended movements (in the order of 0.5 to 5%). Complex patterns of relative phasing were observed between the intended movements and the MM that were characterized by the presence of higher harmonics in the oscillating units. The patterns in question depended on the frequency of the intended movements, which was varied from 0.5 to 3 Hz. At low frequencies, cases of both in- and anti-phase coordination were observed amidst various other instances of phase locking. MM were smaller in the anti-phase than in the in-phase coordination. At higher frequencies, the occurrence of in-phase coordination was most common while instances of anti-phase coordination were absent. To account for these properties, a dynamical model for the coordination between large-amplitude intended movements and small-amplitude MM was derived in the form of a model of nonlinearly coupled nonlinear oscillators with unequal amplitudes. The derived model was shown to correspond well with many quantitative and qualitative features of the observed dynamics of MM, including frequency locking, stable in-phase and anti-phase coordination, coordination-dependency of mirror movement amplitudes, and the presence of higher harmonics. The implications of the obtained experimental and analytical results and numerical parameter optimizations for the study of MM were discussed.

  11. Two numerical models for landslide dynamic analysis

    NASA Astrophysics Data System (ADS)

    Hungr, Oldrich; McDougall, Scott

    2009-05-01

    Two microcomputer-based numerical models (Dynamic ANalysis (DAN) and three-dimensional model DAN (DAN3D)) have been developed and extensively used for analysis of landslide runout, specifically for the purposes of practical landslide hazard and risk assessment. The theoretical basis of both models is a system of depth-averaged governing equations derived from the principles of continuum mechanics. Original features developed specifically during this work include: an open rheological kernel; explicit use of tangential strain to determine the tangential stress state within the flowing sheet, which is both more realistic and beneficial to the stability of the model; orientation of principal tangential stresses parallel with the direction of motion; inclusion of the centripetal forces corresponding to the true curvature of the path in the motion direction and; the use of very simple and highly efficient free surface interpolation methods. Both models yield similar results when applied to the same sets of input data. Both algorithms are designed to work within the semi-empirical framework of the "equivalent fluid" approach. This approach requires selection of material rheology and calibration of input parameters through back-analysis of real events. Although approximate, it facilitates simple and efficient operation while accounting for the most important characteristics of extremely rapid landslides. The two models have been verified against several controlled laboratory experiments with known physical basis. A large number of back-analyses of real landslides of various types have also been carried out. One example is presented. Calibration patterns are emerging, which give a promise of predictive capability.

  12. Bio-Inspired Neural Model for Learning Dynamic Models

    NASA Technical Reports Server (NTRS)

    Duong, Tuan; Duong, Vu; Suri, Ronald

    2009-01-01

    A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

  13. Multiscale modeling with smoothed dissipative particle dynamics.

    PubMed

    Kulkarni, Pandurang M; Fu, Chia-Chun; Shell, M Scott; Leal, L Gary

    2013-06-21

    In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow. PMID:23802949

  14. Models of dynamical R-parity violation

    NASA Astrophysics Data System (ADS)

    Csáki, Csaba; Kuflik, Eric; Slone, Oren; Volansky, Tomer

    2015-06-01

    The presence of R-parity violating interactions may relieve the tension between existing LHC constraints and natural supersymmetry. In this paper we lay down the theoretical framework and explore models of dynamical R-parity violation in which the breaking of R-parity is communicated to the visible sector by heavy messenger fields. We find that R-parity violation is often dominated by non-holomorphic operators that have so far been largely ignored, and might require a modification of the existing searches at the LHC. The dynamical origin implies that the effects of such operators are suppressed by the ratio of either the light fermion masses or the supersymmetry breaking scale to the mediation scale, thereby providing a natural explanation for the smallness of R-parity violation. We consider various scenarios, classified by whether R-parity violation, flavor breaking and/or supersymmetry breaking are mediated by the same messenger fields. The most compact case, corresponding to a deformation of the so called flavor mediation scenario, allows for the mediation of supersymmetry breaking, R-parity breaking, and flavor symmetry breaking in a unified manner.

  15. Analytic wave model of Stark deceleration dynamics

    SciTech Connect

    Gubbels, Koos; Meijer, Gerard; Friedrich, Bretislav

    2006-06-15

    Stark deceleration relies on time-dependent inhomogeneous electric fields which repetitively exert a decelerating force on polar molecules. Fourier analysis reveals that such fields, generated by an array of field stages, consist of a superposition of partial waves with well-defined phase velocities. Molecules whose velocities come close to the phase velocity of a given wave get a ride from that wave. For a square-wave temporal dependence of the Stark field, the phase velocities of the waves are found to be odd-fraction multiples of a fundamental phase velocity {lambda}/{tau}, with {lambda} and {tau} the spatial and temporal periods of the field. Here we study explicitly the dynamics due to any of the waves as well as due to their mutual perturbations. We first solve the equations of motion for the case of single-wave interactions and exploit their isomorphism with those for the biased pendulum. Next we analyze the perturbations of the single-wave dynamics by other waves and find that these have no net effect on the phase stability of the acceleration or deceleration process. Finally, we find that a packet of molecules can also ride a wave which results from an interference of adjacent waves. In this case, small phase stability areas form around phase velocities that are even-fraction multiples of the fundamental velocity. A detailed comparison with classical trajectory simulations and with experiment demonstrates that the analytic 'wave model' encompasses all the longitudinal physics encountered in a Stark decelerator.

  16. Monitoring and modeling growing season dynamics

    NASA Astrophysics Data System (ADS)

    White, Michael Aaron

    Phenology, the study of recurring biological cycles and their connection to climate, is a growing field of global change research. Vegetation phenology exerts a strong control over carbon cycles, weather, and global radiation partitioning between sensible and latent heat fluxes. Phenological monitors of the timing and length of the growing season can also be used as barometers of vegetation responses to climatic variability. In the following chapters, I present research investigating the monitoring and interpretation of growing season dynamics. Ecological modeling is limited more by data availability than by model theory. In particular, the description of vegetation functional types (biomes) for distributed modeling has been lacking. In chapter 1, I present a documented description and sensitivity analysis of the 34 parameters used in the ecosystem model, BIOME-BGC, for major temperate biomes. I applied BIOME-BGC in the eastern U.S. deciduous broad leaf forest and found that minor phenological variation created large impacts on simulated net ecosystem exchange of carbon (chapter 2). In addition to simulating the effects of growing season variability, it is also important to develop accurate field monitoring techniques, both as a means of testing modeling activities and as a validation of satellite remote sensing estimates. I conducted an intercomparison of field techniques that could be used to monitor phenological dynamics in and ecosystems (chapter 3). I found that methodological barriers to rapid, low cost monitoring were severe, but that a digital camera with both visible and near-infrared channels was a viable option. Satellite remote sensing provides the only means of obtaining consistent estimates of phenological variation at a global scale, yet our understanding of these data has been limited by a lack of ground observations. To address this problem, I proposed, developed, and wrote a phenology measurement protocol for the Global Learning and Observations

  17. Assessing Molecular Dynamics Simulations with Solvatochromism Modeling.

    PubMed

    Schwabe, Tobias

    2015-08-20

    For the modeling of solvatochromism with an explicit representation of the solvent molecules, the quality of preceding molecular dynamics simulations is crucial. Therefore, the possibility to apply force fields which are derived with as little empiricism as possible seems desirable. Such an approach is tested here by exploiting the sensitive solvatochromism of p-nitroaniline, and the use of reliable excitation energies based on approximate second-order coupled cluster results within a polarizable embedding scheme. The quality of the various MD settings for four different solvents, water, methanol, ethanol, and dichloromethane, is assessed. In general, good agreement with the experiment is observed when polarizable force fields and special treatment of hydrogen bonding are applied. PMID:26220273

  18. Modeling the dynamics of piano keys

    NASA Astrophysics Data System (ADS)

    Brenon, Celine; Boutillon, Xavier

    2003-10-01

    The models of piano keys available in the literature are crude: two degrees of freedom and a very few dynamical or geometrical parameters. Experiments on different piano mechanisms (upright, grand, one type of numerical keyboard) exhibit strong differences in the two successive phases of the key motion which are controlled by the finger. Understanding the controllability of the escapement velocity (typically a few percents for professional pianists), the differences between upright and grand pianos, the rationale for the numerous independent adjustments by technicians, and the feel by the pianist require sophisticated modeling. In addition to the inertia of the six independently moving parts of a grand piano mechanism, a careful modeling of friction at pivots and between the jack and the roll, of damping and nonlinearities in felts, and of internal springs will be presented. Simulations will be confronted to the measurements of the motions of the different parts. Currently, the first phase of the motion and the transition to the second phase are well understood while some progress must still be made in order to describe correctly this short but important phase before the escapement of the hammer. [Work done in part at the Laboratory for Musical Acoustics, Paris.

  19. Persistent agents in Axelrod's social dynamics model

    NASA Astrophysics Data System (ADS)

    Reia, Sandro M.; Neves, Ubiraci P. C.

    2016-01-01

    Axelrod's model of social dynamics has been studied under the effect of external media. Here we study the formation of cultural domains in the model by introducing persistent agents. These are agents whose cultural traits are not allowed to change but may be spread through local neighborhood. In the absence of persistent agents, the system is known to present a transition from a monocultural to a multicultural regime at some critical Q (number of traits). Our results reveal a dependence of critical Q on the occupation probability p of persistent agents and we obtain the phase diagram of the model in the (p,Q) -plane. The critical locus is explained by the competition of two opposite forces named here barrier and bonding effects. Such forces are verified to be caused by non-persistent agents which adhere (adherent agents) to the set of traits of persistent ones. The adherence (concentration of adherent agents) as a function of p is found to decay for constant Q. Furthermore, adherence as a function of Q is found to decay as a power law with constant p.

  20. CIDGA - Coupling of Interior Dynamic models with Global Atmosphere models

    NASA Astrophysics Data System (ADS)

    Noack, Lena; Plesa, Ana-Catalina; Breuer, Doris

    2010-05-01

    Atmosphere temperatures and in particular the surface temperatures mostly depend on the solar heat flux and the atmospheric composition. The latter can be influenced by interior processes of the planet, i.e. volcanism that releases greenhouse gases such as H2O, CO2 and methane into the atmosphere and plate tectonics through which atmospheric CO2 is recycled via carbonates into the mantle. An increasing concentration of greenhouse gases in the atmosphere results in an increase of the surface temperature. Changes in the surface temperature on the other hand may influence the cooling behaviour of the planet and hence influence its volcanic activity [Phillips et al., 2001]. This feedback relation between mantle convection and atmosphere is not very well understood, since until now mostly either the interior dynamic of a planet or its atmosphere was investigated separately. 2D or 3D mantle convection models to the authors' knowledge haven't been coupled to the atmosphere so far. We have used the 3D spherical simulation code GAIA [Hüttig et al., 2008] including partial melt production and coupled it with the atmosphere module CIDGA using a gray greenhouse model for varying H2O concentrations. This way, not only the influence of mantle dynamics on the atmosphere can be investigated, but also the recoupling effect, that the surface temperature has on the mantle dynamics. So far, we consider one-plate planets without crustal and thus volatile recycling. Phillips et al. [2001] already investigated the coupling effect of the surface temperature on mantle dynamics by using simple parameterized convection models for Venus. In their model a positive feedback mechanism has been observed, i.e., an increase of the surface temperature leads to an increase of partial melt and hence an increase of atmosphere density and surface temperature. Applying our model to Venus, we show that an increase of surface temperature leads not only to an increase of partial melt in the mantle; it also

  1. Dynamical and Physical Models of Ecliptic Comets

    NASA Astrophysics Data System (ADS)

    Dones, L.; Boyce, D. C.; Levison, H. F.; Duncan, M. J.

    2005-08-01

    In most simulations of the dynamical evolution of the cometary reservoirs, a comet is removed from the computer only if it is thrown from the Solar System or strikes the Sun or a planet. However, ejection or collision is probably not the fate of most active comets. Some, like 3D/Biela, disintegrate for no apparent reason, and others, such as the Sun-grazers, 16P/Brooks 2, and D/1993 F2 Shoemaker-Levy 9, are pulled apart by the Sun or a planet. Still others, like 107P/Wilson Harrington and D/1819 W1 Blanpain, are lost and then rediscovered as asteroids. Historically, amateurs discovered most comets. However, robotic surveys now dominate the discovery of comets (http://www.comethunter.de/). These surveys include large numbers of comets observed in a standard way, so the process of discovery is amenable to modeling. Understanding the selection effects for discovery of comets is a key problem in constructing models of cometary origin. To address this issue, we are starting new orbital integrations that will provide the best model to date of the population of ecliptic comets as a function of location in the Solar System and the size of the cometary nucleus, which we expect will vary with location. The integrations include the gravitational effects of the terrestrial and giant planets and, in some cases, nongravitational jetting forces. We will incorporate simple parameterizations for mantling and mass loss based upon detailed physical models. This approach will enable us to estimate the fraction of comets in different states (active, extinct, dormant, or disintegrated) and to track how the cometary size distribution changes as a function of distance from the Sun. We will compare the results of these simulations with bias-corrected models of the orbital and absolute magnitude distributions of Jupiter-family comets and Centaurs.

  2. Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

    PubMed

    Wei, Yu; Li, Jinlong; Chen, Zeming; Wang, Fengwei; Huang, Weiqiang; Hong, Zhangyong; Lin, Jianping

    2015-08-28

    The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protease. The method sequentially applied SVM (Support Vector Machine), shape similarity, pharmacophore modeling and molecular docking. Using a validation set (270 positives, 155,996 negatives), the multistage virtual screening method showed a high hit rate and high enrichment factor of 80.47% and 465.75, respectively. Furthermore, this approach was applied to screen the National Cancer Institute database (NCI), which contains 260,000 molecules. From the final hit list, 6 molecules were selected for further testing in an in vitro HIV-1 protease inhibitory assay, and 2 molecules (NSC111887 and NSC121217) showed inhibitory potency against HIV-1 protease, with IC50 values of 62 μM and 162 μM, respectively. With further chemical development, these 2 molecules could potentially serve as HIV-1 protease inhibitors. PMID:26185005

  3. Identification of the minimum pharmacophore of lipid-phosphatidylserine (PS) binding peptide-peptoid hybrid PPS1D1.

    PubMed

    Singh, Jaspal; Shukla, Satya Prakash; Desai, Tanvi J; Udugamasooriya, D Gomika

    2016-09-15

    We previously reported a unique peptide-peptoid hybrid, PPS1 that specifically recognizes lipid-phosphatidylserine (PS) and a few other negatively charged phospholipids, but not neutral phospholipids, on the cell membrane. The dimeric version of PPS1, i.e., PPS1D1 triggers strong cancer cell cytotoxicity and has been validated in lung cancer models both in vitro and in vivo. Given that PS and other negatively charged phospholipids are abundant in almost all tumor microenvironments, PPS1D1 is an attractive drug lead that can be developed into a globally applicable anti-cancer agent. Therefore, it is extremely important to identify the minimum pharmacophore of PPS1D1. In this study, we have synthesized alanine/sarcosine derivatives as well as truncated derivatives of PPS1D1. We performed ELISA-like competitive binding assay to evaluate the PS-recognition potential and standard MTS cell viability assay on HCC4017 lung cancer cells to validate the cell cytotoxicity effects of these derivatives. Our studies indicate that positively charged residues at the second and third positions, as well as four hydrophobic residues at the fifth through eighth positions, are imperative for the binding and activity of PPS1D1. Methionine at the first position was not essential, whereas the positively charged Nlys at the fourth position was minimally needed, as two derivatives that were synthesized replacing this residue were almost as active as PPS1D1. PMID:27485601

  4. Finite Mixture Dynamic Regression Modeling of Panel Data with Implications for Dynamic Response Analysis

    ERIC Educational Resources Information Center

    Kaplan, David

    2005-01-01

    This article considers the problem of estimating dynamic linear regression models when the data are generated from finite mixture probability density function where the mixture components are characterized by different dynamic regression model parameters. Specifically, conventional linear models assume that the data are generated by a single…

  5. Modelling vegetation dynamics for Alpine meadows

    NASA Astrophysics Data System (ADS)

    Della Chiesa, Stefano; Bertoldi, Giacomo; Wohlfahrt, Georg; Rist, Armin; Niedrist, Georg; Albertson, John D.; Tappeiner, Ulrike

    2010-05-01

    Regional climate scenarios predict a temperature increase and a summer precipitation decrease for the European Alps. This is expected to lead to longer vegetation periods, but also to drought stress in Alpine meadows ecosystems. It is therefore uncertain if the predicted climatic changes will lead to an increase or decrease of biomass production in these grassland ecosystems. Understanding plant growth requires to consider the complex interactions between soil, atmosphere and climate via its physiological properties, in particular LAI, stomatal resistance, rooting depth, albedo, surface roughness and effects on soil moisture. Vegetation Dynamic Models (VDM) coupled with hydrological models take into account these interactions in order to study and estimate biomass production quantitatively. In this contribution, the VDM previously developed by Montaldo et al. (2005) for semi-arid environments is extended to Alpine meadows in the Stubai Valley (Eastern Austria) which are typically not subjected to water and nutrient stresses, but undergoing low temperature limitations. The aim is to assess the model robustness. Moreover, the effects of mowing practice during the season were taken into consideration. The VDM has then been implemented in the distributed hydrological model GEOtop (Rigon et al., 2006). The VDM performed well in the considered case study. The validation and calibration of the model is presented and then the effects of increased temperature and decreased precipitation are investigated numerically. In order to evaluate in the field the effects of climatic change on Alpine grassland biomass production, the inner Alpine continental Mazia Valley (South Tyrol, Italy) has been chosen in 2009 for Long-Term Ecological Research. These climatic changes will be simulated by manipulations along an altitudinal gradient comprising measuring stations at about 1000 m, 1500 m and 2000 m a.s.l.. Meadow monoliths will be transplanted downslope to simulate temperature

  6. An Extension Dynamic Model Based on BDI Agent

    NASA Astrophysics Data System (ADS)

    Yu, Wang; Feng, Zhu; Hua, Geng; WangJing, Zhu

    this paper's researching is based on the model of BDI Agent. Firstly, This paper analyze the deficiencies of the traditional BDI Agent model, Then propose an extension dynamic model of BDI Agent based on the traditional ones. It can quickly achieve the internal interaction of the tradition model of BDI Agent, deal with complex issues under dynamic and open environment and achieve quick reaction of the model. The new model is a natural and reasonable model by verifying the origin of civilization using the model of monkeys to eat sweet potato based on the design of the extension dynamic model. It is verified to be feasible by comparing the extended dynamic BDI Agent model with the traditional BDI Agent Model uses the SWARM, it has important theoretical significance.

  7. Exploring the nonlinear dynamics of a physiologically viable model neuron

    SciTech Connect

    Lindner, J.F.; Ditto, W.L.

    1996-06-01

    We describe efforts underway to explore the nonlinear dynamics of the Pinsky-Rinzel model neuron. Via computer simulations, we seek to discover nonlinear phenomena in this physiologically accurate model, thereby complementing ongoing and future experiments. Here we describe the model in detail and analyze it using tools of nonlinear dynamics to demonstrate nontrivial behaviors. {copyright} {ital 1996 American Institute of Physics.}

  8. Dynamics in Higher Education Politics: A Theoretical Model

    ERIC Educational Resources Information Center

    Kauko, Jaakko

    2013-01-01

    This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…

  9. Stochastic-dynamic Modelling of Morphodynamics

    NASA Astrophysics Data System (ADS)

    Eppel, D. P.; Kapitza, H.

    The numerical prediction of coastal sediment motion over time spans of years and decades is hampered by the sediment's ability, when stirred by waves and currents, to often react not uniquely to the external forcing but rather to show some kind of internal dynamics whose characteristics are not directly linked to the external forcing. Analytical stability analyses of the sediment-water system indicate that instabilities of tidally forced sediment layers in shallow seas can occur on spatial scales smaller than and not related to the scales of the tidal components. The finite growth of these un- stable amplitides can be described in terms of Ginzburg-Landau equations. Examples are the formation of ripples, sand waves and sand dunes or the formation of shore- face connected ridges. Among others, analyses of time series of coastal profiles from Duck, South Carolina extending over several decades gave evidence for self-organized behaviour suggesting that some important sediment-water systems can be perceived as dissipative dynamical structures. The consequences of such behaviour for predicting morphodynamics has been pointed out: one would expect that there exist time horizons beyond which predictions in the traditional deterministic sense are not possible. One would have to look for statistical quantities containing information of some relevance such as phase-space densities of solutions, attractor sets and the like. This contribution is part of an effort to address the prediction problem of morphody- namics through process-oriented models containing stochastic parameterizations for bottom shear stresses, critical shear stresses, etc.; process-based models because they are directly related to the physical processes but in a stochastic form because it is known that the physical processes contain strong stochastic components. The final outcome of such a program would be the generation of an ensemble of solutions by Monte Carlo integrations of the stochastic model

  10. Supercomputer modeling of volcanic eruption dynamics

    SciTech Connect

    Kieffer, S.W.; Valentine, G.A.; Woo, Mahn-Ling

    1995-06-01

    Our specific goals are to: (1) provide a set of models based on well-defined assumptions about initial and boundary conditions to constrain interpretations of observations of active volcanic eruptions--including movies of flow front velocities, satellite observations of temperature in plumes vs. time, and still photographs of the dimensions of erupting plumes and flows on Earth and other planets; (2) to examine the influence of subsurface conditions on exit plane conditions and plume characteristics, and to compare the models of subsurface fluid flow with seismic constraints where possible; (3) to relate equations-of-state for magma-gas mixtures to flow dynamics; (4) to examine, in some detail, the interaction of the flowing fluid with the conduit walls and ground topography through boundary layer theory so that field observations of erosion and deposition can be related to fluid processes; and (5) to test the applicability of existing two-phase flow codes for problems related to the generation of volcanic long-period seismic signals; (6) to extend our understanding and simulation capability to problems associated with emplacement of fragmental ejecta from large meteorite impacts.

  11. A dynamic model of Venus's gravity field

    NASA Technical Reports Server (NTRS)

    Kiefer, W. S.; Richards, M. A.; Hager, B. H.; Bills, B. G.

    1984-01-01

    Unlike Earth, long wavelength gravity anomalies and topography correlate well on Venus. Venus's admittance curve from spherical harmonic degree 2 to 18 is inconsistent with either Airy or Pratt isostasy, but is consistent with dynamic support from mantle convection. A model using whole mantle flow and a high viscosity near surface layer overlying a constant viscosity mantle reproduces this admittance curve. On Earth, the effective viscosity deduced from geoid modeling increases by a factor of 300 from the asthenosphere to the lower mantle. These viscosity estimates may be biased by the neglect of lateral variations in mantle viscosity associated with hot plumes and cold subducted slabs. The different effective viscosity profiles for Earth and Venus may reflect their convective styles, with tectonism and mantle heat transport dominated by hot plumes on Venus and by subducted slabs on Earth. Convection at degree 2 appears much stronger on Earth than on Venus. A degree 2 convective structure may be unstable on Venus, but may have been stabilized on Earth by the insulating effects of the Pangean supercontinental assemblage.

  12. A dynamic model of Venus's gravity field

    NASA Technical Reports Server (NTRS)

    Kiefer, W. S.; Richards, M. A.; Hager, B. H.; Bills, B. G.

    1986-01-01

    Unlike Earth, long wavelength gravity anomalies and topography correlate well on Venus. Venus's admittance curve from spherical harmonic degree 2 to 18 is inconsistent with either Airy or Pratt isostasy, but is consistent with dynamic support from mantle convection. A model using whole mantle flow and a high viscosity near surface layer overlying a constant viscosity mantle reproduces this admittance curve. On Earth, the effective viscosity deduced from geoid modeling increases by a factor of 300 from the asthenosphere to the lower mantle. These viscosity estimates may be biased by the neglect of lateral variations in mantle viscosity associated with hot plumes and cold subducted slabs. The different effective viscosity profiles for Earth and Venus may reflect their convective styles, with tectonism and mantle heat transport dominated by hot plumes on Venus and by subducted slabs on Earth. Convection at degree 2 appears much stronger on Earth than on Venus. A degree 2 convective structure may be unstable on Venus, but may have been stabilized on Earth by the insulating effects of the Pangean supercontinental assemblage.

  13. Research of cyclist's spine dynamical model.

    PubMed

    Griskevicius, Julius; Linkel, Arturas; Pauk, Jolanta

    2014-01-01

    The purpose of the paper is to present a dynamic model of bicyclist's lumbar spine for the evaluation of linear and angular variation of intervertebral distance in sagittal plane. Ten degrees of freedom biomechanical model of the spine was solved numerically. Larger loads acting on a cyclist spine occur mostly while sitting in a sport position in comparison with recreation or middle sitting. The load on lumbar spine region is influenced by cycle's tire pressure, road bumps and wheeling speed. The biggest linear and angular displacements were found between L4-L5 vertebras. The biggest load protractile spine muscle experiences in the sport sitting position. Maximum vertebrae rotation and linear variation values in wheeling regime with 1.5 Bar tyres pressure and at a speed of 10 km/h are 0.46° and 0.46 mm. Maximum vertebrae rotation and linear variation values for a 23 year old, 1.74 m high and 73 kg of mass (bicycle mass~7 kg) man in wheeling regime with 3.5 Bar tyres pressure and at a speed of 30 km/h are 3.9° and 1.23 mm. The biggest variation of rotation in sagittal plane between two nearest lumbar spines is about 1°. Because of this displacement the frontal part of last mentioned disc is compressed with 530 N more and dorsal disc part as much less. PMID:24708161

  14. A dynamical stochastic coupled model for financial markets

    NASA Astrophysics Data System (ADS)

    Govindan, T. E.; Ibarra-Valdez, Carlos; Ruiz de Chávez, J.

    2007-07-01

    A model coupling a deterministic dynamical system which represents trading, with a stochastic one that represents asset prices evolution is presented. Both parts of the model have connections with well established dynamic models in mathematical economics and finance. The main objective is to represent the double feedback between trading dynamics (the demand/supply interaction) and price dynamics (assumed as largely random). We present the model, and address to some extent existence and uniqueness, continuity with respect to initial conditions and stability of solutions. The non-Lipschitz case is briefly considered as well.

  15. AIR INGRESS ANALYSIS: COMPUTATIONAL FLUID DYNAMIC MODELS

    SciTech Connect

    Chang H. Oh; Eung S. Kim; Richard Schultz; Hans Gougar; David Petti; Hyung S. Kang

    2010-08-01

    The Idaho National Laboratory (INL), under the auspices of the U.S. Department of Energy, is performing research and development that focuses on key phenomena important during potential scenarios that may occur in very high temperature reactors (VHTRs). Phenomena Identification and Ranking Studies to date have ranked an air ingress event, following on the heels of a VHTR depressurization, as important with regard to core safety. Consequently, the development of advanced air ingress-related models and verification and validation data are a very high priority. Following a loss of coolant and system depressurization incident, air will enter the core of the High Temperature Gas Cooled Reactor through the break, possibly causing oxidation of the in-the core and reflector graphite structure. Simple core and plant models indicate that, under certain circumstances, the oxidation may proceed at an elevated rate with additional heat generated from the oxidation reaction itself. Under postulated conditions of fluid flow and temperature, excessive degradation of the lower plenum graphite can lead to a loss of structural support. Excessive oxidation of core graphite can also lead to the release of fission products into the confinement, which could be detrimental to a reactor safety. Computational fluid dynamic model developed in this study will improve our understanding of this phenomenon. This paper presents two-dimensional and three-dimensional CFD results for the quantitative assessment of the air ingress phenomena. A portion of results of the density-driven stratified flow in the inlet pipe will be compared with results of the experimental results.

  16. Stochastic hybrid modeling of intracellular calcium dynamics

    NASA Astrophysics Data System (ADS)

    Choi, TaiJung; Maurya, Mano Ram; Tartakovsky, Daniel M.; Subramaniam, Shankar

    2010-10-01

    Deterministic models of biochemical processes at the subcellular level might become inadequate when a cascade of chemical reactions is induced by a few molecules. Inherent randomness of such phenomena calls for the use of stochastic simulations. However, being computationally intensive, such simulations become infeasible for large and complex reaction networks. To improve their computational efficiency in handling these networks, we present a hybrid approach, in which slow reactions and fluxes are handled through exact stochastic simulation and their fast counterparts are treated partially deterministically through chemical Langevin equation. The classification of reactions as fast or slow is accompanied by the assumption that in the time-scale of fast reactions, slow reactions do not occur and hence do not affect the probability of the state. Our new approach also handles reactions with complex rate expressions such as Michaelis-Menten kinetics. Fluxes which cannot be modeled explicitly through reactions, such as flux of Ca2+ from endoplasmic reticulum to the cytosol through inositol 1,4,5-trisphosphate receptor channels, are handled deterministically. The proposed hybrid algorithm is used to model the regulation of the dynamics of cytosolic calcium ions in mouse macrophage RAW 264.7 cells. At relatively large number of molecules, the response characteristics obtained with the stochastic and deterministic simulations coincide, which validates our approach in the limit of large numbers. At low doses, the response characteristics of some key chemical species, such as levels of cytosolic calcium, predicted with stochastic simulations, differ quantitatively from their deterministic counterparts. These observations are ubiquitous throughout dose response, sensitivity, and gene-knockdown response analyses. While the relative differences between the peak-heights of the cytosolic [Ca2+] time-courses obtained from stochastic (mean of 16 realizations) and deterministic

  17. COMPUTATIONAL FLUID DYNAMICS MODELING ANALYSIS OF COMBUSTORS

    SciTech Connect

    Mathur, M.P.; Freeman, Mark; Gera, Dinesh

    2001-11-06

    In the current fiscal year FY01, several CFD simulations were conducted to investigate the effects of moisture in biomass/coal, particle injection locations, and flow parameters on carbon burnout and NO{sub x} inside a 150 MW GEEZER industrial boiler. Various simulations were designed to predict the suitability of biomass cofiring in coal combustors, and to explore the possibility of using biomass as a reburning fuel to reduce NO{sub x}. Some additional CFD simulations were also conducted on CERF combustor to examine the combustion characteristics of pulverized coal in enriched O{sub 2}/CO{sub 2} environments. Most of the CFD models available in the literature treat particles to be point masses with uniform temperature inside the particles. This isothermal condition may not be suitable for larger biomass particles. To this end, a stand alone program was developed from the first principles to account for heat conduction from the surface of the particle to its center. It is envisaged that the recently developed non-isothermal stand alone module will be integrated with the Fluent solver during next fiscal year to accurately predict the carbon burnout from larger biomass particles. Anisotropy in heat transfer in radial and axial will be explored using different conductivities in radial and axial directions. The above models will be validated/tested on various fullscale industrial boilers. The current NO{sub x} modules will be modified to account for local CH, CH{sub 2}, and CH{sub 3} radicals chemistry, currently it is based on global chemistry. It may also be worth exploring the effect of enriched O{sub 2}/CO{sub 2} environment on carbon burnout and NO{sub x} concentration. The research objective of this study is to develop a 3-Dimensional Combustor Model for Biomass Co-firing and reburning applications using the Fluent Computational Fluid Dynamics Code.

  18. Dynamic modelling and analysis of space webs

    NASA Astrophysics Data System (ADS)

    Yu, Yang; Baoyin, HeXi; Li, JunFeng

    2011-04-01

    Future space missions demand operations on large flexible structures, for example, space webs, the lightweight cable nets deployable in space, which can serve as platforms for very large structures or be used to capture orbital objects. The interest in research on space webs is likely to increase in the future with the development of promising applications such as Furoshiki sat-ellite of JAXA, Robotic Geostationary Orbit Restorer (ROGER) of ESA and Grapple, Retrieve And Secure Payload (GRASP) of NASA. Unlike high-tensioned nets in civil engineering, space webs may be low-tensioned or tensionless, and extremely flexible, owing to the microgravity in the orbit and the lack of support components, which may cause computational difficulties. Mathematical models are necessary in the analysis of space webs, especially in the conceptual design and evaluation for prototypes. A full three-dimensional finite element (FE) model was developed in this work. Trivial truss elements were adopted to reduce the computational complexity. Considering cable is a compression-free material and its tensile stiffness is also variable, we introduced the cable material constitutive relationship to work out an accurate and feasible model for prototype analysis and design. In the static analysis, the stress distribution and global deformation of the webs were discussed to get access to the knowledge of strength of webs with different types of meshes. In the dynamic analysis, special attention was paid to the impact problem. The max stress and global deformation were investigated. The simulation results indicate the interesting phenomenon which may be worth further research.

  19. Bayesian Estimation of Random Coefficient Dynamic Factor Models

    ERIC Educational Resources Information Center

    Song, Hairong; Ferrer, Emilio

    2012-01-01

    Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…

  20. A dynamic model for the Lagrangian stochastic dispersion coefficient

    SciTech Connect

    Pesmazoglou, I.; Navarro-Martinez, S.; Kempf, A. M.

    2013-12-15

    A stochastic sub-grid model is often used to accurately represent particle dispersion in turbulent flows using large eddy simulations. Models of this type have a free parameter, the dispersion coefficient, which is not universal and is strongly grid-dependent. In the present paper, a dynamic model for the evaluation of the coefficient is proposed and validated in decaying homogeneous isotropic turbulence. The grid dependence of the static coefficient is investigated in a turbulent mixing layer and compared to the dynamic model. The dynamic model accurately predicts dispersion statistics and resolves the grid-dependence. Dispersion statistics of the dynamically calculated constant are more accurate than any static coefficient choice for a number of grid spacings. Furthermore, the dynamic model produces less numerical artefacts than a static model and exhibits smaller sensitivity in the results predicted for different particle relaxation times.

  1. Dynamic hysteretic sensing model of bending-mode Galfenol transducer

    SciTech Connect

    Cao, Shuying Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei

    2015-05-07

    A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.

  2. Spatiotemporal modelling of viral infection dynamics

    NASA Astrophysics Data System (ADS)

    Beauchemin, Catherine

    Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than

  3. Dynamic force matching: A method for constructing dynamical coarse-grained models with realistic time dependence

    SciTech Connect

    Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.

    2015-04-21

    Coarse-grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse-grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse-graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. In this paper, we consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse-graining (MS-CG) method of Voth and coworkers. We propose a method of converting a MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that were studied by Zwanzig [J. Stat. Phys. 9, 215 (1973)]. The properties of the fictitious particles can be inferred from analysis of the dynamics of all-atom simulations of the system of interest. This is analogous to the fact that the MS-CG method generates the CG potential from analysis of equilibrium structures observed in all-atom simulation data. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics programs. We present tests of this method on a series of simple examples that demonstrate that

  4. System Dynamics Modeling for Supply Chain Information Sharing

    NASA Astrophysics Data System (ADS)

    Feng, Yang

    In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

  5. A dynamic fault tree model of a propulsion system

    NASA Technical Reports Server (NTRS)

    Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila

    2006-01-01

    We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

  6. Space Station Freedom solar dynamic modules structural modelling and analysis

    SciTech Connect

    Lawrence, C.; Morris, R.

    1991-12-01

    In support of the Space Station Freedom (SSF) Solar Dynamic Power Module effort, structural design studies were performed to investigate issues related to the design of the power module, its pointing capabilities, and the integration of the module into the SSF infrastructure. Of particular concern from a structural viewpoint are the dynamics of the power module, the impact of the power module on the Space Station dynamics and controls, and the required control effort for obtaining the specified Solar Dynamic Power Module pointing accuracy. Structural analyses were performed to determine the structural dynamics attributes of both the existing and the proposed structural dynamics module designs. The objectives of these analyses were to generate validated Solar Dynamic Power Module NASTRAN finite element models, combine Space Station and power module models into integrated system models, perform finite element modal analyses to assess the effect of the relocations of the power module center of mass, and provide modal data to controls designers for control systems design.

  7. High content pharmacophores from molecular fields: a biologically relevant method for comparing and understanding ligands.

    PubMed

    Cheeseright, Timothy J; Mackey, Mark D; Scoffin, Robert A

    2011-09-01

    The question of how and why a small molecule binds to a protein is central to ligand-based drug discovery. The traditional way of approaching these questions is pharmacophore analysis. However, pharmacophores as usually applied lack quantitation and subtlety. An improvement is to consider the electrostatic and steric fields of the ligand directly. Molecular fields provide a rich view of the potential interactions that a molecule can make and can be validated through experimental data on molecular interactions and through quantum mechanics calculations. A technique is presented in this review for comparing molecules using molecular fields and assigning similarity scores. This high information content method can be used to align molecules for SAR analysis, to determine the bioactive conformation from ligand data, and to screen large libraries of compounds for structurally unrelated actives. An extension to allow interactive exploration of chemistry space via bioisostere analysis is also reviewed. Examples from the literature showing the success of these methods are presented, and future directions discussed. PMID:21726191

  8. The FlexX database docking environment--rational extraction of receptor based pharmacophores.

    PubMed

    Claussen, Holger; Gastreich, Marcus; Apelt, Volker; Greene, Jonathan; Hindle, Sally A; Lemmen, Christian

    2004-01-01

    We present an integrated docking environment that allows for iterative and interactive detailed analysis of many docking solutions. All docking information is stored in an ORACLE database. New scoring schemes (e.g. target-specific scoring functions) as well as various types of filters can be easily defined and tested within this environment. As an example application we investigated the validity of the following hypothesis: If a docking procedure can lead to enrichments significantly better than random then a bias towards (partially) correct placements should be detectable. Such bias in terms of a preference for certain interacting groups within the active site can be used to select a set of receptor-based pharmacophore constraints, which in turn might be used to enhance the docking procedure. As a proof of concept for this approach we performed docking studies on three targets: thrombin, the cyclin-dependent kinase 2 (CDK2) and the angiotensin converting enzyme (ACE). We docked a set of known active compounds with standard FlexX and derived three sets of target-specific receptor-based