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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. Dynamics based pharmacophore models for screening potential inhibitors of mycobacterial cyclopropane synthase.

    PubMed

    Choudhury, Chinmayee; Priyakumar, U Deva; Sastry, G Narahari

    2015-04-27

    The therapeutic challenges in the treatment of tuberculosis demand multidisciplinary approaches for the identification of potential drug targets as well as fast and accurate techniques to screen huge chemical libraries. Mycobacterial cyclopropane synthase (CmaA1) has been shown to be essential for the survival of the bacteria due to its critical role in the synthesis of mycolic acids. The present study proposes pharmacophore models based on the structure of CmaA1 taking into account its various states in the cyclopropanation process, and their dynamic nature as assessed using molecular dynamics (MD) simulations. The qualities of these pharmacophore models were validated by mapping 23 molecules that have been previously reported to exhibit inhibitory activities on CmaA1. Additionally, 1398 compounds that have been shown to be inactive for tuberculosis were collected from the ChEMBL database and were screened against the models for validation. The models were further validated by comparing the results from pharmacophore mapping with the results obtained from docking these molecules with the respective protein structures. The best models are suggested by validating all the models based on their screening abilities and by comparing with docking results. The models generated from the MD trajectories were found to perform better than the one generated based on the crystal structure demonstrating the importance of incorporating receptor flexibility in drug design.

  4. Dynamic pharmacophore model optimization: identification of novel HIV-1 integrase inhibitors.

    PubMed

    Deng, Jinxia; Sanchez, Tino; Neamati, Nouri; Briggs, James M

    2006-03-01

    We extended the previously described dynamic pharmacophore model studies of HIV-1 integrase (IN) by considering more key residues in the active site, including Mg2+. First, we applied a Monte Carlo sampling method to map the complementary features of the IN binding surface. Two types of dynamic pharmacophore models were generated. One considers Mg2+ as part of the IN and therefore as an excluded volume, and the other treats Mg2+ as a positively charged feature, representing a new type of pharmacophore model aimed to identify compounds potentially preventing Mg2+ binding. Second, we validated the models with 385 known active (IC50 < 20 microM) and 235 (IC50 > 100 microM) inactive IN inhibitors. Third, we used the derived models to screen our small molecule database. Twenty-two structurally novel compounds were tested in an in vitro assay specific for IN, and two of them showed IC50 < or = 10 microM for strand transfer reaction.

  5. Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

    PubMed

    John, Shalini; Thangapandian, Sundarapandian; Lee, Keun Woo

    2012-01-01

    Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations. PMID:22292952

  6. Dynamic structure-based pharmacophore model development: a new and effective addition in the histone deacetylase 8 (HDAC8) inhibitor discovery.

    PubMed

    Thangapandian, Sundarapandian; John, Shalini; Lee, Yuno; Kim, Songmi; Lee, Keun Woo

    2011-01-01

    Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design. PMID:22272142

  7. Dynamic and multi-pharmacophore modeling for designing polo-box domain inhibitors.

    PubMed

    Sakkiah, Sugunadevi; Senese, Silvia; Yang, Qianfan; Lee, Keun Woo; Torres, Jorge Z

    2014-01-01

    The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics.

  8. Discovery of Potential Inhibitors of Aldosterone Synthase from Chinese Herbs Using Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation Studies

    PubMed Central

    Lu, Fang; Qiao, Liansheng; Chen, Xi; Li, Gongyu

    2016-01-01

    Aldosterone synthase (CYP11B2) is a key enzyme for the biosynthesis of aldosterone, which plays a significant role for the regulation of blood pressure. Excess aldosterone can cause the dysregulation of the renin-angiotensin-aldosterone system (RAAS) and lead to hypertension. Therefore, research and development of CYP11B2 inhibitor are regarded as a novel approach for the treatment of hypertension. In this study, the pharmacophore models of CYP11B2 inhibitors were generated and the optimal model was used to identify potential CYP11B2 inhibitors from the Traditional Chinese Medicine Database (TCMD, Version 2009). The hits were further refined by molecular docking and the interactions between compounds and CYP11B2 were analyzed. Compounds with high Fitvalue, high docking score, and expected interactions with key residues were selected as potential CYP11B2 inhibitors. Two most promising compounds, ethyl caffeate and labiatenic acid, with high Fitvalue and docking score were reserved for molecular dynamics (MD) study. All of them have stability of ligand binding which suggested that they might perform the inhibitory effect on CYP11B2. This study provided candidates for novel drug-like CYP11B2 inhibitors by molecular simulation methods for the hypertension treatment. PMID:27781210

  9. 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

  10. Identification of Potent Virtual Leads Specific to S1' Loop of ADAMTS4: Pharmacophore Modeling, 3D-QSAR, Molecular Docking and Dynamic Studies.

    PubMed

    Suganya, P Rathi; Kalva, Sukesh; Saleena, Lilly M

    2016-01-01

    ADAMTS4 (Aggrecanase-1) is an important enzyme, which belongs to ADAMTS family. Aggrecanase-1 is involved in aggrecan degradation of articular cartilage in osteoarthritis and rheumatoid arthritis. Overall variability of S1' domain of ADAMTS4 has been the main selectivity determinant to design the unique inhibitors. 34 inhibitors from Binding database and literature were used to develop the pharmacophore model. The five featured pharmacophore model AHHRR had the best survival score of 3.493 and post-hoc score of 2.545, indicating that the model is highly reliable. The 3D-QSAR acquired had excellent r(2) value of 0.99 and GH score of 0.839. The validated pharmacophore model was used for insilico screening of Asinex and ZINC database for finding the potential lead compounds. ZINC00987406 and ASN04459656 which pose high glide score i.e >7 Kcal/mol and H-bond and hydrophobic interactions in the S1'loop residues of ADAMTS4 were subjected to Molecular Dynamics Simulation studies. Molecular dynamic simulation result indicates that the RMSD and RMSF of backbone atoms for the above complexes were within the limit of 2.0 A˚. These compounds can be potential candidates for osteoarthritis by inhibiting ADAMTS4. PMID:26813685

  11. A combination of pharmacophore modeling, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on PDE4 enzyme inhibitors.

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2016-11-01

    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 pyrazolopyridine and quinoline derivatives using Schrödinger suite 2014-3. A four-point pharmacophore model was developed using 74 molecules having pIC50 ranging from 10.1 to 4.5. The best four feature model consists of one hydrogen bond acceptor, two aromatic rings, and one hydrophobic group. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R(2 )= .9949), cross validation coefficient (Q(2 )= .7291), and Pearson-r (.9107) at six component partial least square factor. The external validation indicated that our QSAR model possessed high predictive power with R(2) value of .88. The generated model was further validated by enrichment studies using the decoy test. Molecular docking, free energy calculation, and molecular dynamics (MD) simulation studies have been performed to explore the putative binding modes of these ligands. A 10-ns MD simulation confirmed the docking results of both stability of the 1XMU-ligand complex and the presumed active conformation. Outcomes of the present study provide insight in designing novel molecules with better PDE4 inhibitory activity.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. DrugOn: a fully integrated pharmacophore modeling and structure optimization toolkit

    PubMed Central

    Megalooikonomou, Vasileios; Makris, Christos

    2015-01-01

    During the past few years, pharmacophore modeling has become one of the key components in computer-aided drug design and in modern drug discovery. DrugOn is a fully interactive pipeline designed to exploit the advantages of modern programming and overcome the command line barrier with two friendly environments for the user (either novice or experienced in the field of Computer Aided Drug Design) to perform pharmacophore modeling through an efficient combination of the PharmACOphore, Gromacs, Ligbuilder and PDB2PQR suites. Our platform features a novel workflow that guides the user through each logical step of the iterative 3D structural optimization setup and drug design process. For the pharmacophore modeling we are focusing on either the characteristics of the receptor or the full molecular system, including a set of selected ligands. DrugOn can be freely downloaded from our dedicated server system at www.bioacademy.gr/bioinformatics/drugon/. PMID:25648563

  19. 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

  20. 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.

  1. 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

  2. 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

  3. Discovery of novel Myc-Max heterodimer disruptors with a three-dimensional pharmacophore model.

    PubMed

    Mustata, Gabriela; Follis, Ariele Viacava; Hammoudeh, Dalia I; Metallo, Steven J; Wang, Huabo; Prochownik, Edward V; Lazo, John S; Bahar, Ivet

    2009-03-12

    A three-dimensional pharmacophore model was generated utilizing a set of known inhibitors of c-Myc-Max heterodimer formation. The model successfully identified a set of structurally diverse compounds with potential inhibitory activity against c-Myc. Nine compounds were tested in vitro, and four displayed affinities in the micromolar range and growth inhibitory activity against c-Myc-overexpressing cells. These studies demonstrate the applicability of pharmacophore modeling to the identification of novel and potentially more puissant inhibitors of the c-Myc oncoprotein.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Pharmacophore Modeling and Molecular Docking Studies on Pinus roxburghii as a Target for Diabetes Mellitus

    PubMed Central

    Kaushik, Pawan; Lal Khokra, Sukhbir; Rana, A. C.

    2014-01-01

    The present study attempts to establish a relationship between ethnopharmacological claims and bioactive constituents present in Pinus roxburghii against all possible targets for diabetes through molecular docking and to develop a pharmacophore model for the active target. The process of molecular docking involves study of different bonding modes of one ligand with active cavities of target receptors protein tyrosine phosphatase 1-beta (PTP-1β), dipeptidyl peptidase-IV (DPP-IV), aldose reductase (AR), and insulin receptor (IR) with help of docking software Molegro virtual docker (MVD). From the results of docking score values on different receptors for antidiabetic activity, it is observed that constituents, namely, secoisoresinol, pinoresinol, and cedeodarin, showed the best docking results on almost all the receptors, while the most significant results were observed on AR. Then, LigandScout was applied to develop a pharmacophore model for active target. LigandScout revealed that 2 hydrogen bond donors pointing towards Tyr 48 and His 110 are a major requirement of the pharmacophore generated. In our molecular docking studies, the active constituent, secoisoresinol, has also shown hydrogen bonding with His 110 residue which is a part of the pharmacophore. The docking results have given better insights into the development of better aldose reductase inhibitor so as to treat diabetes related secondary complications. PMID:25114678

  12. Pharmacophore Modeling and Molecular Docking Studies on Pinus roxburghii as a Target for Diabetes Mellitus.

    PubMed

    Kaushik, Pawan; Lal Khokra, Sukhbir; Rana, A C; Kaushik, Dhirender

    2014-01-01

    The present study attempts to establish a relationship between ethnopharmacological claims and bioactive constituents present in Pinus roxburghii against all possible targets for diabetes through molecular docking and to develop a pharmacophore model for the active target. The process of molecular docking involves study of different bonding modes of one ligand with active cavities of target receptors protein tyrosine phosphatase 1-beta (PTP-1β), dipeptidyl peptidase-IV (DPP-IV), aldose reductase (AR), and insulin receptor (IR) with help of docking software Molegro virtual docker (MVD). From the results of docking score values on different receptors for antidiabetic activity, it is observed that constituents, namely, secoisoresinol, pinoresinol, and cedeodarin, showed the best docking results on almost all the receptors, while the most significant results were observed on AR. Then, LigandScout was applied to develop a pharmacophore model for active target. LigandScout revealed that 2 hydrogen bond donors pointing towards Tyr 48 and His 110 are a major requirement of the pharmacophore generated. In our molecular docking studies, the active constituent, secoisoresinol, has also shown hydrogen bonding with His 110 residue which is a part of the pharmacophore. The docking results have given better insights into the development of better aldose reductase inhibitor so as to treat diabetes related secondary complications. PMID:25114678

  13. 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

  14. 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.

  15. Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling

    PubMed Central

    Kumar, Raj; Son, Minky; Bavi, Rohit; Lee, Yuno; Park, Chanin; Arulalapperumal, Venkatesh; Cao, Guang Ping; Kim, Hyong-ha; Suh, Jung-keun; Kim, Yong-seong; Kwon, Yong Jung; Lee, Keun Woo

    2015-01-01

    Aim: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. Methods: The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. Results: The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Conclusion: Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors. PMID:26051108

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

    PubMed

    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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Pharmacophore modeling improves virtual screening for novel peroxisome proliferator-activated receptor-gamma ligands

    PubMed Central

    Lewis, Stephanie N.; Garcia, Zulma; Hontecillas, Raquel; Bassaganya-Riera, Josep; Bevan, David R.

    2015-01-01

    Peroxisome proliferator-activated receptor-gamma (PPARγ) is a nuclear hormone receptor involved in regulating various metabolic and immune processes. The PPAR family of receptors possesses a large binding cavity that imparts promiscuity of ligand binding not common to other nuclear receptors. This feature increases the challenge of using computational methods to identify PPAR ligands that will dock favorably into a structural model. Utilizing both ligand- and structure-based pharmacophore methods, we sought to improve agonist prediction by grouping ligands according to pharmacophore features, and pairing models derived from these features with receptor structures for docking. For 22 of the 33 receptor structures evaluated we observed an increase in true positive rate (TPR) when screening was restricted to compounds sharing molecular features found in rosiglitazone. A combination of structure models used for docking resulted in a higher TPR (40%) when compared to docking with a single structure model (less than 20%). Prediction was also improved when specific protein-ligand interactions between the docked ligands and structure models were given greater weight than the calculated free energy of binding. A large-scale screen of compounds using a marketed drug database verified the predictive ability of the selected structure models. This study highlights the steps necessary to improve screening for PPARγ ligands using multiple structure models, ligand-based pharmacophore data, evaluation of protein-ligand interactions, and comparison of docking datasets. The unique combination of methods presented here holds potential for more efficient screening of compounds with unknown affinity for PPARγ that could serve as candidates for therapeutic development. PMID:25616366

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

    PubMed Central

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

    2015-01-01

    B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q2 = 0.621, r2pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained. PMID:26035757

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 3D QSAR Studies, Pharmacophore Modeling and Virtual Screening on a Series of Steroidal Aromatase Inhibitors

    PubMed Central

    Xie, Huiding; Qiu, Kaixiong; Xie, Xiaoguang

    2014-01-01

    Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q2 = 0.636, r2ncv = 0.988, r2pred = 0.658; CoMSIA: q2 = 0.843, r2ncv = 0.989, r2pred = 0.601). This 3D QSAR approach provides significant insights that can be used to develop novel and potent SAIs. In addition, Genetic algorithm with linear assignment of hypermolecular alignment of database (GALAHAD) was used to derive 3D pharmacophore models. The selected pharmacophore model contains two acceptor atoms and four hydrophobic centers, which was used as a 3D query for virtual screening against NCI2000 database. Six hit compounds were obtained and their biological activities were further predicted by the CoMFA and CoMSIA models, which are expected to design potent and novel SAIs. PMID:25405729

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Pharmacophores in Drug Research.

    PubMed

    Langer, Thierry

    2010-07-12

    The pharmacophore concept in modern drug research is highlighted and the most important use examples and success stories are reviewed. These include papers from method development as well as from application areas. As indicated by the number of publications available, the pharmacophore approach has proven to be extremely useful as interface between medicinal and computational chemistry, both in virtual screening and library design for efficient hit discovery, but also in the optimization of lead compounds to clinical candidates. Recent studies focus on the usage of parallel screening using pharmacophore models for bio-activity profiling and early stage risk assessment of potential side effects and toxicity due to interaction of drug candidates with anti-targets. PMID:27463325

  4. 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

  5. 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

  6. The high affinity melationin binding site probed with conformationally restricted ligand--I. Pharmacophore and minireceptor models.

    PubMed

    Jansen, J M; Copinga, S; Gruppen, G; Molinari, E J; Dubocovich, M L; Grol, C J

    1996-08-01

    The affinities of enantiomers of conformationally restricted melatonin analogues for the ML-1 and ML-2 putative melatonin receptor subtypes are reported. Most ligands exhibited reversed stereoselectivity when competing with 125I 2-iodomelatonin binding to chicken retinal (ML-1) and hamster brain (ML-2) membranes, further supporting the biochemical and pharmacological differences reported for these two sites. Based on the data for the ML-1 site and thorough conformational analyses of several ligands, two pharmacophore models were derived using the program APOLLO. The pharmacophoric elements included were putative receptor points from the amide NH, the amide CO, and the methoxy-O, together with the normal through the phenyl ring. The large drop in ML-1 affinity observed for 4-methoxy-2-acetamido-indan (6a) could not be explained from either of these models. Minireceptors were subsequently built around the two pharmacophores using Yak. Analysis of the resulting ligand-minireceptor interactions offered an explanation for the low affinity of 6a and allowed one of the pharmacophore models to be selected for use in future drug design. PMID:8879554

  7. Constructing an atomic-resolution model of human P2X7 receptor followed by pharmacophore modeling to identify potential inhibitors.

    PubMed

    Ahmadi, Mehdi; Nowroozi, Amin; Shahlaei, Mohsen

    2015-09-01

    The P2X purinoceptor 7 (P2X7R) is a trimeric ATP-activated ion channel gated by extracellular ATP. P2X7R has important role in numerous diseases including pain, neurodegeneration, and inflammatory diseases such as rheumatoid arthritis and osteoarthritis. In this prospective, the discovery of small-molecule inhibitors for P2X7R as a novel therapeutic target has received considerable attention in recent years. At first, 3D structure of P2X7R was built by using homology modeling (HM) and a 50ns molecular dynamics simulation (MDS). Ligand-based quantitative pharmacophore modeling methodology of P2X7R antagonists were developed based on training set of 49 compounds. The best four-feature pharmacophore model, includes two hydrophobic aromatic, one hydrophobic and one aromatic ring features, has the highest correlation coefficient (0.874), cost difference (368.677), low RMSD (2.876), as well as it shows a high goodness of fit and enrichment factor. Consequently, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. Among these compounds, six potential molecule were identified as potential virtual leads which, as such or upon further optimization, can be used to design novel P2X7R inhibitors.

  8. Isoxazole analogues bind the system xc- transporter: structure-activity relationship and pharmacophore model.

    PubMed

    Patel, Sarjubhai A; Rajale, Trideep; O'Brien, Erin; Burkhart, David J; Nelson, Jared K; Twamley, Brendan; Blumenfeld, Alex; Szabon-Watola, Monika I; Gerdes, John M; Bridges, Richard J; Natale, Nicholas R

    2010-01-01

    Analogues of amino methylisoxazole propionic acid (AMPA), were prepared from a common intermediate 12, including lipophilic analogues using lateral metalation and electrophilic quenching, and were evaluated at System xc-. Both the 5-naphthylethyl-(16) and 5-naphthylmethoxymethyl-(17) analogues adopt an E-conformation in the solid state, yet while the former has robust binding at System xc-, the latter is virtually devoid of activity. The most potent analogues were amino acid naphthyl-ACPA 7g, and hydrazone carboxylic acid, 11e Y=Y'=3,5-(CF(3))(2), which both inhibited glutamate uptake by the System xc- transporter with comparable potency to the endogenous substrate cystine, whereas in contrast the closed isoxazolo[3,4-d] pyridazinones 13 have significantly lower activity. A preliminary pharmacophore model has been constructed to provide insight into the analogue structure-activity relationships.

  9. 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

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

    PubMed

    Ekins, Sean; Madrid, Peter B; Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh; Freundlich, Joel S

    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.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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.

  16. Pharmacophore modeling, virtual screening, and in vitro testing reveal haloperidol, eprazinone, and fenbutrazate as neurokinin receptors ligands.

    PubMed

    Krautscheid, Yvonne; Senning, Carl Johann Åke; Sartori, Simone B; Singewald, Nicolas; Schuster, Daniela; Stuppner, Hermann

    2014-06-23

    Neurokinin receptors (NKRs) have been shown to be involved in many physiological processes, rendering them promising novel drug targets, but also making them the possible cause for side effects of several drugs. Aiming to answer the question whether the binding to NKRs could have a share in the side effects or even the desired effects of already licensed drugs, we generated a set of ligand-based common feature pharmacophore models based on the structural information about subtype-selective and nonselective NKR antagonists and screened an in-house database mainly composed of licensed drugs. The prospective pharmacological investigations of the virtual hits haloperidol, eprazinone, and fenbutrazate confirmed them to be NKR ligands in vitro. By the identification of licensed drugs as so far unknown NKR ligands, this study contributes to establishing an activity profile of the investigated compounds and confirms the presented pharmacophore models as useful tools for this purpose. PMID:24849814

  17. 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

  18. 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.

  19. MexAB-OprM specific efflux pump inhibitors in Pseudomonas aeruginosa. Part 3: Optimization of potency in the pyridopyrimidine series through the application of a pharmacophore model.

    PubMed

    Nakayama, Kiyoshi; Kawato, Haruko; Watanabe, Jun; Ohtsuka, Masami; Yoshida, Ken-ichi; Yokomizo, Yoshihiro; Sakamoto, Atsunobu; Kuru, Noriko; Ohta, Toshiharu; Hoshino, Kazuki; Yoshida, Kumi; Ishida, Hiroko; Cho, Aesop; Palme, Monica H; Zhang, Jason Z; Lee, Ving J; Watkins, William J

    2004-01-19

    The addition of substituents to the pyridopyrimidine scaffold of MexAB-OprM specific efflux pump inhibitors was explored. As predicted by a pharmacophore model, the incorporation substituents at the 2-position improved potency. Piperidines were found to be optimal, and further introduction of polar groups without compromising the activity was shown to be feasible. Careful positioning of the essential acidic moiety of the pharmacophore relative to the scaffold led to the discovery of vinyl tetrazoles with still greater potency.

  20. 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

  1. 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

  2. Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

    PubMed

    Lin, Chun-Yuan; 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 (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) 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.

  3. Pharmacophore Model To Discover OX1 and OX2 Orexin Receptor Ligands.

    PubMed

    Turku, Ainoleena; Borrel, Alexandre; Leino, Teppo O; Karhu, Lasse; Kukkonen, Jyrki P; Xhaard, Henri

    2016-09-22

    Small molecule agonists and antagonists of the orexinergic system have key implications for research and therapeutic purposes. We report a pharmacophore model trained on ∼200 antagonists and prospectively validated by screening a collection of ∼137,000 compounds. The resulting hit list, 395 compounds, was tested for OX1 and OX2 receptor activity using calcium mobilization assay in recombinant cell lines. Validation was conducted using both calcium mobilization and [(125)I]-orexin-A competition binding. Compounds 4-7 have weak agonist activity and Ki's in the 1-30 μM range; compounds 8-14 are antagonists with Ki's in the 0.1-10 μM range for OX2 and 1-50 μM for the OX1 receptor. Docking simulations were used to devise a working hypothesis where two subpockets are important for activation, one between TM5 and TM6 lined by Phe5.42, Tyr5.47, and Tyr6.48 and another above the orthosteric pocket lined by Asp2.65 and Tyr7.32. PMID:27546834

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Pharmacophore Modeling and Molecular Docking Studies of potential inhibitors to E6 PBM–PDZ from Human Papilloma Virus (HPV)

    PubMed Central

    Tian, Yu-Shi; Kawashita, Norihito; Arai, Yuki; Okamoto, Kousuke; Takagi, Tatsuya

    2015-01-01

    High-risk human papillomaviruses (HPVs) are known to cause cervical cancer. Vaccines are now available to prevent HPV infection. However, a clinically approved drug is yet not available to treat HPV. The PDZ(PSD−95/Dlg/ZO−1)−binding motif (PBM) in the E6 protein of HPVs targets the PDZ domain (known to be associated with oncogenesis) for degradation. Therefore, it is of interest to study PBM–PDZ interaction towards its possible inhibition with a potential inhibitor. Thus, four pharmocophore models of PBM−PDZ complex were developed. In order to obtain potent small molecules for its inhibition, a commercial compound database was screened using both these pharmacophore models and molecule docking method. These efforts identified four potential compounds (1−4) towards its inhibition with the docking scores range -18.2 to -15.0. PMID:26420921

  15. Pharmacophore Modeling and Molecular Docking Studies of potential inhibitors to E6 PBM-PDZ from Human Papilloma Virus (HPV).

    PubMed

    Tian, Yu-Shi; Kawashita, Norihito; Arai, Yuki; Okamoto, Kousuke; Takagi, Tatsuya

    2015-01-01

    High-risk human papillomaviruses (HPVs) are known to cause cervical cancer. Vaccines are now available to prevent HPV infection. However, a clinically approved drug is yet not available to treat HPV. The PDZ(PSD-95/Dlg/ZO-1)-binding motif (PBM) in the E6 protein of HPVs targets the PDZ domain (known to be associated with oncogenesis) for degradation. Therefore, it is of interest to study PBM-PDZ interaction towards its possible inhibition with a potential inhibitor. Thus, four pharmocophore models of PBM-PDZ complex were developed. In order to obtain potent small molecules for its inhibition, a commercial compound database was screened using both these pharmacophore models and molecule docking method. These efforts identified four potential compounds (1-4) towards its inhibition with the docking scores range -18.2 to -15.0. PMID:26420921

  16. Development of a pharmacophore model for the catecholamine release-inhibitory peptide catestatin: virtual screening and functional testing identify novel small molecule therapeutics of hypertension.

    PubMed

    Tsigelny, Igor F; Kouznetsova, Valentina L; Biswas, Nilima; Mahata, Sushil K; O'Connor, Daniel T

    2013-09-15

    The endogenous catecholamine release-inhibitory peptide catestatin (CST) regulates events leading to hypertension and cardiovascular disease. Earlier we studied the structure of CST by NMR, molecular modeling, and amino acid scanning mutagenesis. That structure has now been exploited for elucidation of interface pharmacophores that mediate binding of CST to its target, with consequent secretory inhibition. Designed pharmacophore models allowed screening of 3D structural domains. Selected compounds were tested on both cultured catecholaminergic cells and an in vivo model of hypertension; in each case, the candidates showed substantial mimicry of native CST actions, with preserved or enhanced potency and specificity. The approach and compounds have thus enabled rational design of novel drug candidates for treatment of hypertension or autonomic dysfunction.

  17. Constrained NBMPR Analogue Synthesis, Pharmacophore Mapping and 3D-QSAR Modeling of Equilibrative nucleoside Transporter 1 (ENT1) Inhibitory Activity

    PubMed Central

    Zhu, Zhengxiang; Buolamwini, John K.

    2009-01-01

    Conformationally constrained analogue synthesis was undertaken to aid in pharmacophore mapping and 3D QSAR analysis of nitrobenzylmercaptopurine riboside (NBMPR) congeners as equilibriative nucleoside transporter 1 (ENT1) inhibitors. In our previous study (Zhu et al., J. Med. Chem. 46, 831–837, 2003), novel regioisomeric nitro-1, 2, 3, 4-tetrahydroisoquinoline conformationally constrained analogues of NBMPR were synthesized and evaluated as ENT1 ligands. 7-NO2-1, 2, 3, 4-tetrahydroisoquino-2-yl purine riboside was identified as the analogue with the nitro group in the best orientation at the NBMPR binding site of ENT1. In the present study, further conformational constraining was introduced by synthesizing 5′-O, 8-cyclo derivatives. The flow cytometrically determined binding affinities indicated that the additional 5′-O, 8-cyclo constraining was unfavorable for binding to the ENT1 transporter. The structure-activity relationship (SAR) acquired was applied to pharmacophore mapping using the PHASE program. The best pharmacophore hypothesis obtained embodied an anti-conformation with three H-bond acceptors, one hydrophobic center, and two aromatic rings involving the 3′-OH, 4′-oxygen, the NO2 group, the benzyl phenyl and the imidazole and pyrimidine portions of the purine ring, respectively. A PHASE 3D-QSAR model derived with this pharmacophore yielded an r2 of 0.916 for four (4) PLS components, and an excellent external test set predictive r2 of 0.78 for 39 compounds. This pharmacophore was used for molecular alignment in a comparative molecular field analysis (CoMFA) 3D-QSAR study that also afforded a predictive model with external test set validation predictive r2 of 0.73. Thus, although limited, this study suggests that the bioactive conformation for NBMPR at the ENT1 transporter could be anti. The study has also suggested an ENT1 inhibitory pharmacophore, and established a predictive CoMFA 3D-QSAR model that might be useful for novel ENT1 inhibitor

  18. Multi-Generational Pharmacophore Modeling for Ligands to the Cholane Steroid-Recognition Site in the β1 Modulatory Subunit of the BKCa Channel

    PubMed Central

    McMillan, Jacob E.; Bukiya, Anna N.; Terrell, Camisha L.; Patil, Shivaputra A.; Miller, Duane D.; Dopico, Alex M.; Parrill, Abby L.

    2014-01-01

    Large conductance, voltage- and Ca2+-gated K+ (BKCa) channels play a critical role in smooth muscle contractility and thus represent an emerging therapeutic target for drug development to treat vascular disease, gastrointestinal, bladder and uterine disorders. Several compounds are known to target the ubiquitously expressed BKCa channel-forming α subunit. In contrast, just a few are known to target the BKCa modulatory β1 subunit, which is highly expressed in smooth muscle and scarce in most other tissues. Lack of available high-resolution structural data makes structure-based pharmacophore modeling of β1 subunit-dependent BKCa channel activators a major challenge. Following recent discoveries of novel BKCa channel activators that act via β1 subunit recognition, we performed ligand-based pharmacophore modeling that led to the successful creation and fine-tuning of a pharmacophore over several generations. Initial models were developed using physiologically active cholane steroids (bile acids) as template. However, as more compounds that act on BKCa β1 have been discovered, our model has been refined to improve accuracy. Database searching with our best-performing model has uncovered several novel compounds as candidate BKCa β1 subunit ligands. Eight of the identified compounds were experimentally screened and two proved to be activators of recombinant BKCa β1 complexes. One of these activators, sobetirome, differs substantially in structure from any previously reported activator. PMID:25459769

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. In silico-based combinatorial pharmacophore modelling and docking studies of GSK-3β and GK inhibitors of Hippophae.

    PubMed

    Middha, Sushil Kumar; Goyal, Arvind Kumar; Faizan, Syed Ahmed; Sanghamitra, Nethramurthy; Basistha, Bharat Chandra; Usha, Talambedu

    2013-11-01

    Type 2 diabetes is an inevitably progressive disease, with irreversible beta cell failure. Glycogen synthase kinase and Glukokinase, two important enzymes with diverse biological actions in carbohydrate metabolism, are promising targets for developing novel antidiabetic drugs. A combinatorial structure-based molecular docking and pharmacophore modelling study was performed with the compounds of Hippophae salicifolia and H. rhamnoides as inhibitors. Docking with Discovery Studio 3.5 revealed that two compounds from H. salicifolia, viz Lutein D and an analogue of Zeaxanthin, and two compounds from H. rhamnoides, viz Isorhamnetin-3-rhamnoside and Isorhamnetin-7-glucoside, bind significantly to the GSK-3 beta receptor and play a role in its inhibition; whereas in the case of Glucokinase, only one compound from both the plants, i.e. vitamin C, had good binding characteristics capable of activation. The results help to understand the type of interactions that occur between the ligands and the receptors. Toxicity predictions revealed that none of the compounds had hepatotoxic effects and had good absorption as well as solubility characteristics. The compounds did not possess plasma protein-binding, crossing blood-brain barrier ability. Further, in vivo and in vitro studies need to be performed to prove that these compounds can be used effectively as antidiabetic drugs. PMID:24287660

  6. In-vitro Antiproliferative Activity of New Tetrahydroisoquinolines (THIQs) on Ishikawa Cells and their 3D Pharmacophore Models

    PubMed Central

    Eyunni, Suresh Kumar V. K.; Gangapuram, Madhavi; Redda, Kinfe K

    2014-01-01

    The antiproliferative activities of new substituted tetrahydroisoquinolines (THIQs) are described. Their cytotoxicities against Ishikawa human endometrial cell line were determined after 72 h drug expose employing Celtiter-Glo assay at concentrations ranging from 0.01 to 100,000 nM. The antiproliferative activities of the compounds understudy were compared to tamoxifen (TAM). In-vitro results indicated that most of the compounds showed better activity than TAM. The most active compounds obtained in this study were 1, 2, 3 and 22 whose IC50 values are 1.41, 0.91, 0.74 and 0.36 μM respectively. This study helped us to evaluate the risk of developing endometrial cancer in the design of non-steroid estrogen receptor modulators with no agonistic effects on uterus. In-silico pharmacophore hypotheses were generated using GALAHAD and PHASE and the best models with a probable bioactive conformation(s) for these compounds were proposed. These conformations and the alignments of the molecular structures give us an insight in designing compounds with better biological activity. PMID:25506297

  7. 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

  8. Characterization of an inhibitory dynamic pharmacophore for the ERCC1-XPA interaction using a combined molecular dynamics and virtual screening approach.

    PubMed

    Barakat, Khaled H; Torin Huzil, J; Luchko, Tyler; Jordheim, Lars; Dumontet, Charles; Tuszynski, Jack

    2009-09-01

    Combination chemotherapy involving Cisplatin is a standard treatment for many cancers. However, following an initial positive response, patients will often relapse, presenting with Cisplatin-resistant disease. One possible mechanism for the acquired resistance to Cisplatin is an increase in DNA repair through the up-regulation of ERCC1, an essential component of the nucleotide excision repair complex. Recruitment of ERCC1 to the site of DNA damage is coordinated through its interaction with a protein known as XPA. As there are currently no effective inhibitors of this interaction, inhibition of the ERCC1/XPA interaction may provide an effective strategy for overcoming the development of Cisplatin-resistant cancers. To discover small molecule inhibitors of this interaction, we have screened both the NCI diversity set of ligands and DrugBank-small molecules against the XPA binding site in ERCC1. These compounds were screened using two different techniques in AUTODOCK to account for receptor flexibility. First, using a set of flexible residues, as determined from MD simulations of the XPA/ERCC1 complex and second, using the relaxed complex scheme implemented by performing independent docking experiments against an ensemble of target conformations that were generated from MD simulations. Lowest energy poses from the two different methods were then used to construct a pharmacophore model, which was then validated by comparison to UCN-01, a weak inhibitor of ERCC1 mediated nucleotide excision.

  9. Generation of N-methyl-D-aspartate agonist and competitive antagonist pharmacophore models. Design and synthesis of phosphonoalkyl-substituted tetrahydroisoquinolines as novel antagonists.

    PubMed

    Ortwine, D F; Malone, T C; Bigge, C F; Drummond, J T; Humblet, C; Johnson, G; Pinter, G W

    1992-04-17

    The preparation and binding affinity of a series of tetrahydroisoquinoline carboxylic acids at the N-methyl-D-aspartate (NMDA) subtype of the glutamate receptor is described, together with a molecular modeling analysis of NMDA agonists and antagonists. Using published NMDA ligands, the active analogue mapping approach was employed in the generation of an agonist pharmacophore model. Although known competitive antagonists such as CPP (1) could be superimposed onto the agonist model, to overcome the assumption that they bind to the same receptor site, an independent modeling approach was used to derive a separate pharmacophore model. Development of a competitive antagonist model involved a stepwise approach that included the definition of a preferred geometry for PO3H2-receptor interactions, multiple conformational searches, and the determination of volume and electronic tolerances. This model, which is described in detail, is consistent with observed affinities of potent NMDA antagonists and has provided an explanation for the observed periodicity in affinities for the known antagonists AP5, AP6, and AP7. The features of the agonist and antagonist models are compared, and hypotheses advanced about the nature of the receptor interactions for these two classes of compounds. The pharmacophore models reported herein are consistent with a single recognition site at the NMDA receptor that can accommodate both agonist and antagonist ligands. To assist in first defining and later exploring the predictive power of the competitive antagonist model, a series of conformationally constrained NMDA antagonist (phosphonoalkyl)tetrahydroisoquinoline-1- and 3-carboxylates was prepared. From this work, 1,2,3,4-tetrahydro-5-(2-phosphonoethyl)-3- isoquinolinecarboxylic acid (89) was identified as the most active lead structure, with an IC50 of 270 nM in [3H]CPP binding. The synthesis and structure-activity relationships of these novel antagonists are described.

  10. Identification of Novel Small-Molecule Agonists for Human Formyl Peptide Receptors and Pharmacophore Models of Their RecognitionS⃞

    PubMed Central

    Kirpotina, Liliya N.; Khlebnikov, Andrei I.; Schepetkin, Igor A.; Ye, Richard D.; Rabiet, Marie-Josèphe; Jutila, Mark A.

    2010-01-01

    N-formyl peptide receptor (FPR1) and N-formyl peptide receptor-like 1 (FPRL1, now known as FPR2) are G protein-coupled receptors involved in host defense and sensing cellular dysfunction. Because of the potential for FPR1/FPR2 as a therapeutic target, our recent high-throughput screening efforts have focused on the identification of unique nonpeptide agonists of FPR1/FPR2. In the present studies, we screened a chemolibrary of drug-like molecules for their ability to induce intracellular calcium mobilization in RBL-2H3 cells transfected with human FPR1 or FPR2. Screening of these compounds resulted in the identification of novel and potent agonists that activated both FPR1 and FPR2, as well as compounds that were specific for either FPR1 or FPR2 with EC50 values in the low micromolar range. Specificity of the compounds was supported by analysis of calcium mobilization in HL-60 cells transfected with human FPR1 and FPR2. In addition, all but one agonist activated intracellular calcium flux and chemotaxis in human neutrophils, irrespective of agonist specificity for FPR1 or FPR2. Molecular modeling of the group of FPR1 and FPR2 agonists using field point methodology allowed us to create pharmacophore models for ligand binding sites and formulate requirements for these specific N-formyl peptide receptor agonists. These studies further demonstrate that agonists of FPR1/FPR2 include compounds with wide chemical diversity and that analysis of such compounds can enhance our understanding of their ligand/receptor interaction. PMID:19903830

  11. 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

  12. 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

  13. 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

    2016-06-13

    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.

  14. 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

  15. QSAR studies of the pyrethroid insecticides. Part 3. A putative pharmacophore derived using methodology based on molecular dynamics and hierarchical cluster analysis.

    PubMed

    Ford, Martyn G; Hoare, Neil E; Hudson, Brian D; Nevell, Thomas G; Banting, Lee

    2002-08-01

    Previous studies of the conformational behaviour of a group of synthetic pyrethroid insecticides have been extended to a more structurally diverse set. This includes compounds with different backbones and differing stereochemistry, with both Types I and II biological activity. These compounds also encompass a large range of biological activities. A parameterisation of the CHARMM force field for these compounds has been performed and the extra parameters are reported. Conformational sampling, using molecular dynamics (MD), has been performed for each of the 41 active structures. The accessible conformations of each have been characterised by the values of the common torsion angles using hierarchichal cluster analysis (HCA). A further CA, based on the centroids derived from the conformational sampling, identified a conformation common to at least 39 of the 41 structures. The critical torsion angles of this conformation lie at the centre of the molecule about the ester linkage and are defining an extended conformation, which differs from the minimum energy conformation of deltamethrin used previously. This may represent a putative pharmacophore for kill. The methods used here improve significantly on those used previously. The CHARMM force field was parameterised for the compounds and an improved method of conformational sampling, based on centroid clustering, has also been used.

  16. 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

  17. 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.

  18. 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.

  19. Pharmacophore modeling of nilotinib as an inhibitor of ATP-binding cassette drug transporters and BCR-ABL kinase using a three-dimensional quantitative structure-activity relationship approach.

    PubMed

    Shukla, Suneet; Kouanda, Abdul; Silverton, Latoya; Talele, Tanaji T; Ambudkar, Suresh V

    2014-07-01

    Nilotinib (Tasigna) is a tyrosine kinase inhibitor approved by the FDA to treat chronic phase chronic myeloid leukemia patients. It is also a transport substrate of the ATP-binding cassette (ABC) drug efflux transporters ABCB1 (P-glycoprotein, P-gp) and ABCG2 (BCRP), which may have an effect on the pharmacokinetics and toxicity of this drug. The goal of this study was to identify pharmacophoric features of nilotinib in order to potentially develop specific inhibitors of BCR-ABL kinase with minimal interactions with ABC drug transporters. Three-dimensional pharmacophore modeling and quantitative structure-activity relationship (QSAR) studies were carried out on a series of nilotinib analogues to identify chemical features that contribute to inhibitory activity of nilotinib against BCR-ABL kinase activity, P-gp, and ABCG2. Twenty-five derivatives of nilotinib were synthesized and were then tested to measure their activity to inhibit BCR-ABL kinase and to inhibit the function of ABC drug transporters. A set of in vitro experiments including kinase activity and cell-based transport assays and photolabeling of P-gp and ABCG2 with a transport substrate, [(125)I]-iodoarylazido-prazosin (IAAP), were carried out in isolated membranes to evaluate the potency of the derivatives to inhibit the function of ABC drug transporters and BCR-ABL kinase. Sixteen, fourteen, and ten compounds were selected as QSAR data sets, respectively, to generate PHASE v3.1 pharmacophore models for BCR-ABL kinase, ABCG2, and P-gp inhibitors. The IC50 values of these derivatives against P-gp, ABCG2, or BCR-ABL kinase were used to generate pharmacophore features required for optimal interactions with these targets. A seven-point pharmacophore (AADDRRR) for BCR-ABL kinase inhibitory activity, a six-point pharmacophore (ADHRRR) for ABCG2 inhibitory activity, and a seven-point pharmacophore (AADDRRR) for P-gp inhibitory activity were generated. The derived models clearly demonstrate high predictive power

  20. Ligand based pharmacophoric modelling and docking of bioactive pyrazolium 3-nitrophthalate (P3NP) on Bacillus subtilis, Aspergillus fumigatus and Aspergillus niger - Computational and Hirshfeld surface analysis.

    PubMed

    Balachandar, S; Sethuram, M; Muthuraja, P; Shanmugavadivu, T; Dhandapani, M

    2016-10-01

    Biologically active Lewis acid-base compound, pyrazolium 3-nitro phthalate (P3NP) has been synthesized and crystallized by slow evaporation - solution method at 30°C. Spectral and single crystal X-Ray diffraction (XRD) were used to characterize the compound. The stability of the P3NP was confirmed by UV-Visible spectral analysis. P3NP crystallizes in monoclinic P21/C space group with cell parameters, a=13.009 (3) Å, b=12.584 (3) Å, c=7.529 (18) Å and β=93.052 (4)(o) with Z=4. Crystal packing was stabilized by N(+)H⋯O(-), OH⋯O and CH⋯O intermolecular hydrogen bonds. The nature of anion - cation interactions and crystal packing from various types of intermolecular contacts and their importance were explored using the Hirshfeld surface analysis. The structure was optimized by Density Functional Theory at B3LYP level with 6-311++G(d,p) basis set and the vibrational frequencies were theoretically calculated. Band gap between Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) and Electrostatic potential (ESP) were calculated. Antimicrobial activities of P3NP with targets were clinically tested and were found to exhibit antibacterial activity against gram positive and antifungal activity against pathogens with Minimum Inhibitory Concentration (MIC). Ligand based pharmacophore modelling was used to understand the potential of P3NP ligand to bind with selected target proteins. iGEM Dock was used to predict the modes of interactions of the ligand with target proteins of the microbes predicted from pharmacophore. PreADMET predicts no absorption of ligand in Human Intestinal Absorption (HIA). PMID:27614246

  1. 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

  2. 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.

  3. PharmDock: a pharmacophore-based docking program

    PubMed Central

    2014-01-01

    Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock. PMID:24739488

  4. 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

  5. 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

  6. 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.

  7. 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

  8. The discovery of a novel and selective inhibitor of PTP1B over TCPTP: 3D QSAR pharmacophore modeling, virtual screening, synthesis, and biological evaluation.

    PubMed

    Ma, Ying; Jin, Yuan-Yuan; Wang, Ye-Liu; Wang, Run-Ling; Lu, Xin-Hua; Kong, De-Xin; Xu, Wei-Ren

    2014-06-01

    Given the special role of insulin and leptin signaling in various biological responses, protein-tyrosine phosphatase-1B (PTP1B) was regarded as a novel therapeutic target for treating type 2 diabetes and obesity. However, owing to the highly conserved (sequence identity of about 74%) in active pocket, targeting PTP1B for drug discovery is a great challenge. In this study, we employed the software package Discovery Studio to develop 3D QSAR pharmacophore models for PTP1B and TCPTP inhibitors. It was further validated by three methods (cost analysis, test set prediction, and Fisher's test) to show that the models can be used to predict the biological activities of compounds without costly and time-consuming synthesis. The criteria for virtual screening were also validated by testing the selective PTP1B inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective inhibitor of PTP1B over TCPTP. After that, a most likely binding mode was proposed. Thus, the findings reported here may provide a new strategy in discovering selective PTP1B inhibitors.

  9. 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

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

    PubMed

    Chaudhari, Prashant; Bari, Sanjay

    2016-02-01

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

  11. 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.

  12. 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

  13. Tubulin inhibitor identification by bioactive conformation alignment pharmacophore-guided virtual screening.

    PubMed

    Nagarajan, Shanthi; Choi, Min Jeong; Cho, Yong Seo; Min, Sun-Joon; Keum, Gyochang; Kim, Soo Jin; Lee, Chang Sik; Pae, Ae Nim

    2015-11-01

    Microtubules are important cellular component that are critical for proper cellular function. Microtubules are synthesized by polymerization of αβ tubulin heterodimers called protofilaments. Microtubule dynamics facilitate proper cell division during mitosis. Disruption of microtubule dynamics by small-molecule agents inhibits mitosis, resulting in apoptotic cell death and preventing cell cycle progression. To identify a novel small molecule that binds the αβ tubulin interface to affect microtubule dynamics, we developed a bioactive conformation alignment pharmacophore (BCAP) model to screen tubulin inhibitors from a huge database. The application of BCAP model generated based on the known αβ-tubulin interface binders enabled us to identify several small-molecules that cause apoptosis in human promyelocytic leukemia (HL-60) cells. Virtual screening combined with an in vitro assay yielded 15 cytotoxic molecules. In particular, ethyl 2-(4-(5-methyl-3-nitro-1H-pyrazol-1-yl)butanamido)-4-phenylthiophene-3-carboxylate (H05) inhibited tubulin polymerization with an IC50 of 17.6 μm concentration. The virtual screening results suggest that the application of an unbiased BCAP pharmacophore greatly eliminates unlikely compounds from a huge database and maximizes screening success. From the limited compounds tested in the tubulin polymerization inhibitor (TPI) assay, compound H05 was discovered as a tubulin inhibitor. This compound requires further structure activity optimization to identify additional potent inhibitors from the same class of molecules.

  14. 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

  15. GRID-based three-dimensional pharmacophores II: PharmBench, a benchmark data set for evaluating pharmacophore elucidation methods.

    PubMed

    Cross, Simon; Ortuso, Francesco; Baroni, Massimo; Costa, Giosuè; Distinto, Simona; Moraca, Federica; Alcaro, Stefano; Cruciani, Gabriele

    2012-10-22

    To date, published pharmacophore elucidation approaches typically use a handful of data sets for validation: here, we have assembled a data set for 81 targets, containing 960 ligands aligned using their cocrystallized protein targets, to provide the experimental "gold standard". The two-dimensional structures are also assembled to remove conformational bias; an ideal method would be able to take these structures as input, find the common features, and reproduce the bioactive conformations and their alignments to correspond with the X-ray-determined gold standard alignments. Here we present this data set and describe three objective measures to evaluate performance: the ability to identify the bioactive conformation, the ability to identify and correctly align this conformation for 50% of the molecules in each data set, and the pharmacophoric field similarity. We have applied this validation methodology to our pharmacophore elucidation method FLAPpharm, that is published in the first paper of this series and discuss the limitations of the data set and objective success criteria. Starting from two-dimensional structures and producing unbiased models, FLAPpharm was able to identify the bioactive conformations for 67% of the ligands and also to produce successful models according to the second metric for 67% of the Pharmbench data sets. Inspection of the unsuccessful models highlighted the limitation of this root mean square (rms)-derived metric, since many were found to be pharmacophorically reasonable, increasing the overall success rate to 83%. The PharmBench data set is available at http://www.moldiscovery.com/PharmBench , along with a web service to enable users to score model alignments coming from external methods in the same way that we have presented here and, therefore, establishes a pharmacophore elucidation benchmark data set available to be used by the community.

  16. Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

    PubMed Central

    Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

    2014-01-01

    Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

  17. Pharmacophore modeling, molecular docking, QSAR, and in silico ADMET studies of gallic acid derivatives for immunomodulatory activity.

    PubMed

    Yadav, Dharmendra Kumar; Khan, Feroz; Negi, Arvind Singh

    2012-06-01

    Immunomodulation refers to an alteration in the immune response due to the intrusion of foreign molecules into the body. In the present communication, QSAR and docking studies of gallic acid derivatives were performed in relation to their immunomodulatory activities. Screening through the use of a QSAR model suggested that the compounds G-4, G-7, G-9, G-10, G-12, and G-13 possess immunomodulatory activity. Activity was predicted using a statistical model developed by the forward stepwise multiple linear regression method. The correlation coefficient (r(2)) and the prediction accuracy (rCV(2)) of the QSAR model were 0.99 and 0.96, respectively. The QSAR study indicated that chemical descriptors-dipole moment, steric energy, amide group count, λ(max) (UV-visible) and molar refractivity-are well correlated with activity, while decreases in the dipole moment, steric energy, and molar refractivity were negatively correlated. A molecular docking study showed that the compounds had high binding affinities for the INFα-2, IL-6, and IL-4 receptors. Binding site residues formed H-bonds with the designed gallic acid derivatives G-3, G-4, G-5, G-6, G-7, and G-10. Moreover, based on screening for oral bioavailability, in silico ADME, and toxicity risk assessment, we concluded that compound G-7 exhibits marked immunomodulatory activity, comparable to levamisole.

  18. History and evolution of the pharmacophore concept in computer-aided drug design.

    PubMed

    Güner, Osman F

    2002-12-01

    With computer-aided drug design established as an integral part of the lead discovery and optimization process, pharmacophores have become a focal point for conceptualizing and understanding receptor-ligand interactions. In the structure-based design process, pharmacophores can be used to align molecules based on the three-dimensional arrangement of chemical features or to develop predictive models (e.g., 3D-QSAR) that correlate with the experimental activities of a given training set. Pharmacophores can be also used as search queries for retrieving potential leads from structural databases, for designing molecules with specific desired attributes, or as fingerprints for assessing similarity and diversity of molecules. This review article presents a historical perspective on the evolution and use of the pharmacophore concept in the pharmaceutical, biotechnology, and fragrances industry with published examples of how the technology has contributed and advanced the field. PMID:12470283

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. Snooker: a structure-based pharmacophore generation tool applied to class A GPCRs.

    PubMed

    Sanders, Marijn P A; Verhoeven, Stefan; de Graaf, Chris; Roumen, Luc; Vroling, Bas; Nabuurs, Sander B; de Vlieg, Jacob; Klomp, Jan P G

    2011-09-26

    G-protein coupled receptors (GPCRs) are important drug targets for various diseases and of major interest to pharmaceutical companies. The function of individual members of this protein family can be modulated by the binding of small molecules at the extracellular side of the structurally conserved transmembrane (TM) domain. Here, we present Snooker, a structure-based approach to generate pharmacophore hypotheses for compounds binding to this extracellular side of the TM domain. Snooker does not require knowledge of ligands, is therefore suitable for apo-proteins, and can be applied to all receptors of the GPCR protein family. The method comprises the construction of a homology model of the TM domains and prioritization of residues on the probability of being ligand binding. Subsequently, protein properties are converted to ligand space, and pharmacophore features are generated at positions where protein ligand interactions are likely. Using this semiautomated knowledge-driven bioinformatics approach we have created pharmacophore hypotheses for 15 different GPCRs from several different subfamilies. For the beta-2-adrenergic receptor we show that ligand poses predicted by Snooker pharmacophore hypotheses reproduce literature supported binding modes for ∼75% of compounds fulfilling pharmacophore constraints. All 15 pharmacophore hypotheses represent interactions with essential residues for ligand binding as observed in mutagenesis experiments and compound selections based on these hypotheses are shown to be target specific. For 8 out of 15 targets enrichment factors above 10-fold are observed in the top 0.5% ranked compounds in a virtual screen. Additionally, prospectively predicted ligand binding poses in the human dopamine D3 receptor based on Snooker pharmacophores were ranked among the best models in the community wide GPCR dock 2010.

  7. [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

  8. 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.

  9. 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

  10. Enclosure fire dynamics model

    NASA Technical Reports Server (NTRS)

    Bellan, J.

    1979-01-01

    A practical situation of an enclosure fire is presented and why the need for a fire dynamic model is addressed. The difficulties in establishing a model are discussed, along with a brief review of enclosure fire models available. The approximation of the practical situation and the model developed are presented.

  11. 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.

  12. 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

  13. 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…

  14. 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

  15. 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.

  16. [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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Model for macroevolutionary dynamics.

    PubMed

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

    2013-07-01

    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

  3. Model for macroevolutionary dynamics.

    PubMed

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

    2013-07-01

    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.

  4. 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.

  5. 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

  6. 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

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

    PubMed

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

    2007-03-01

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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. Modeling Soil Freezing Dynamics

    NASA Astrophysics Data System (ADS)

    Flerchinger, G. N.; Seyfried, M. S.; Hardegree, S. P.

    2002-12-01

    Seasonally frozen soil strongly influences runoff and erosion on large areas of land around the world. In many areas, rain or snowmelt on seasonally frozen soil is the single leading cause of severe runoff and erosion events. As soils freeze, ice blocks the soil pores, greatly diminishing the permeability of the soil. This is aggravated by the tendency of water to migrate to the freezing front, causing elevated ice content and frost heave. Freezing and thawing of the soil are controlled by the complex interactions of heat and water transfer at the soil surface governed by meteorological and environmental conditions at the soil-atmosphere interface. Soil freezing dynamics including liquid water content, infiltration, and runoff simulated by the Simultaneous Heat and Water (SHAW) Model were tested at three field locations in southwest Idaho. Sites included: three soil types at the Orchard Field Test Site; bare and sagebrush-covered runoff plots at the Lower Sheep Creek site on the Reynolds Creek Experimental Watershed; and runoff plots on steep mountainous slopes on the Boise Front. Detailed simulations of soil freezing and thawing were conducted specifically to examine the dynamics of liquid water content during freezing and thawing. Freezing/thawing processes, including liquid water content and runoff, were simulated well.

  14. Pharmacophore-Based Virtual Screening to Discover New Active Compounds for Human Choline Kinase α1.

    PubMed

    Serrán-Aguilera, Lucía; Nuti, Roberto; López-Cara, Luisa C; Mezo, Miguel Á Gallo; Macchiarulo, Antonio; Entrena, Antonio; Hurtado-Guerrero, Ramón

    2015-06-01

    Choline kinase (CK) catalyses the transfer of the ATP γ-phosphate to choline to generate phosphocholine and ADP in the presence of magnesium leading to the synthesis of phosphatidylcholine. Of the three isoforms of CK described in humans, only the α isoforms (HsCKα) are strongly associated with cancer and have been validated as drug targets to treat this disease. Over the years, a large number of Hemicholinium-3 (HC-3)-based HsCKα biscationic inhibitors have been developed though the relevant common features important for the biological function have not been defined. Here, selecting a large number of previous HC-3-based inhibitors, we discover through computational studies a pharmacophore model formed by five moieties that are included in the 1-benzyl-4-(N-methylaniline)pyridinium fragment. Using a pharmacophore-guided virtual screening, we then identified 6 molecules that showed binding affinities in the low μM range to HsCKα1. Finally, protein crystallization studies suggested that one of these molecules is bound to the choline and ATP-binding sites. In conclusion, we have developed a pharmacophore model that not only allowed us to dissect the structural important features of the previous HC-3 derivatives, but also enabled the identification of novel chemical tools with good ligand efficiencies to investigate the biological functions of HsCKα1. PMID:27490389

  15. A Substrate Pharmacophore for the Human Sodium Taurocholate Co-transporting Polypeptide

    PubMed Central

    Dong, Zhongqi; Ekins, Sean; Polli, James E.

    2014-01-01

    Human Sodium Taurocholate Co-transporting Polypeptide (NTCP) is the main bile acid uptake transporter in the liver with the capability to translocate xenobiotics. While its inhibitor requirements have been recently characterized, its substrate requirements have not. The objectives of this study were a) to elucidate NTCP substrate requirements using native bile acids and bile acid analogs, b) to develop the first pharmacophore for NTCP substrates and compare it with the inhibitor pharmacophores, and c) to identify additional NTCP novel substrates. Thus, 18 native bile acids and two bile acid conjugates were initially assessed for NTCP inhibition and/or uptake, which suggested a role of hydroxyl pattern and steric interaction in NTCP binding and translocation. A common feature pharmacophore for NTCP substrate uptake was developed, using 14 native bile acids and bile acid conjugates, yielding a model which featured three hydrophobes, one hydrogen bond donor, one negative ionizable feature and three excluded volumes. This model was used to search a database of FDA approved drugs and retrieved the majority of the known NTCP substrates. Among the retrieved drugs, irbesartan and losartan were identified as novel NTCP substrates, suggesting a potential role of NTCP in drug disposition. PMID:25448570

  16. 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.

  17. 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

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

    PubMed

    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.

  19. 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.

  20. 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

  1. A new strategy based on pharmacophore-based virtual screening in adenosine deaminase inhibitors detection and in-vitro study

    PubMed Central

    2012-01-01

    Background and the purpose of the study Adenosine deaminase (ADA) inhibition not only may be applied for the treatment of ischemic injury, hypertension, lymphomas and leukaemia, but also they have been considered as anti- inflammatory drugs. On the other hand according to literatures, ADA inhibitors without a nucleoside framework would improve pharmacokinetics and decrease toxicity. Hence we have carried out a rational pharmacophore design for non-nucleoside inhibitors filtration. Methods A merged pharmacophore model based on the most potent non-nucleoside inhibitor erythro-9-(2-hydroxy-3-nonyl) adenine (EHNA) and natural products were generated and applied for compounds filtration. The effects of filtrated compounds based on pharmacophore and docking studies investigated on ADA by UV and Fluorescence spectroscopy techniques. Results Extracted compounds were find efficiently inhibit ADA, and the most potent (2) shows an inhibition constant equal to 20 μM. Besides, Fluorescence spectroscopy studies revealed that enzyme 3D structure bear further change in lower concentrations of compound 2. Conclusion 3 non-nucleoside inhibitors for ADA are presented. According to obtained results from UV and fluorescence spectroscopy, such interesting pharmacophore template with multiple approaches will help us to extract or design compound with desired properties. PMID:23351306

  2. Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach.

    PubMed

    Bhadauriya, Anuseema; Dhoke, Gaurao V; Gangwal, Rahul P; Damre, Mangesh V; Sangamwar, Abhay T

    2013-02-01

    Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme that plays a vital role in obesity-induced type 2 diabetes and fatty acid metabolism. To identify dual inhibitors of Acetyl-CoA carboxylase1 and Acetyl-CoA carboxylase2, a pharmacophore modelling approach has been employed. The best HypoGen pharmacophore model for ACC2 inhibitors (Hypo1_ACC2) consists of one hydrogen bond acceptor, one hydrophobic aliphatic and one hydrophobic aromatic feature, whereas the best pharmacophore (Hypo1_ACC1) for ACC1 consists of one additional hydrogen-bond donor (HBD) features. The best pharmacophore hypotheses were validated by various methods such as test set, decoy set and Cat-Scramble methodology. The validated pharmacophore models were used to screen several small-molecule databases, including Specs, NCI, ChemDiv and Natural product databases to identify the potential dual ACC inhibitors. The virtual hits were then subjected to several filters such as estimated [Formula: see text] value, quantitative estimation of drug-likeness and molecular docking analysis. Finally, three novel compounds with diverse scaffolds were selected as potential starting points for the design of novel dual ACC inhibitors.

  3. 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.

  4. Launch Vehicle Dynamics Demonstrator Model

    NASA Technical Reports Server (NTRS)

    1963-01-01

    Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Dynamic Eye Model.

    ERIC Educational Resources Information Center

    Journal of Science and Mathematics Education in Southeast Asia, 1981

    1981-01-01

    Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)

  13. 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

  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. 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.

  16. 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

  17. Structural dynamics system model reduction

    NASA Technical Reports Server (NTRS)

    Chen, J. C.; Rose, T. L.; Wada, B. K.

    1987-01-01

    Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.

  18. 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

  19. p38 Mitogen-activated protein kinase inhibitors: a review on pharmacophore mapping and QSAR studies.

    PubMed

    Gangwal, Rahul P; Bhadauriya, Anuseema; Damre, Mangesh V; Dhoke, Gaurao V; Sangamwar, Abhay T

    2013-01-01

    p38 mitogen-activated protein (MAP) kinases are the serine/threonine protein kinases, which play a vital role in cellular responses to external stress signals. p38 MAP kinase inhibitors have shown anti-inflammatory effects in the preclinical disease models, primarily through inhibition of the expression of inflammatory mediators. A number of structurally diverse p38 MAP kinase inhibitors have been developed as potential anti-inflammatory agents. Most of the inhibitors have failed in the clinical trials either due to poor pharmacokinetic profile or selectivity issue, which makes p38 MAP kinase a promising target for molecular modelling studies. Several quantitative structure activity relationships (QSAR) and pharmacophore models have been developed to identify the structural requirements essential for p38 MAP kinase inhibitory activity. In this review, we provide an overview of the presently known p38 MAP kinase inhibitors and how QSAR analyses among series of compounds have led to the development of molecular models and pharmacophores, allowing the design of novel inhibitors.

  20. IAQ evaluation by dynamic modeling

    SciTech Connect

    Meckler, M.

    1995-12-01

    The current ASHRAE Standard 62-1989, in addition to the ventilation rate (VR) procedure, now contains an alternative procedure in Appendix E to achieve acceptable indoor air quality (IAQ). In this article, the author develops a dynamic model for each of the seven most commonly used HVAC systems listed in Appendix E of ASHRAE Standard 62-1989 and demonstrates how these dynamic models work by providing an illustrative example. In this example, the author estimates the concentration of formaldehyde as a function of time in an office occupancy for three types of filters and outlines how to choose filters to decrease outside air flow requirements.

  1. 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.

  2. Multiscale modeling of nucleosome dynamics.

    PubMed

    Sharma, Shantanu; Ding, Feng; Dokholyan, Nikolay V

    2007-03-01

    Nucleosomes form the fundamental building blocks of chromatin. Subtle modifications of the constituent histone tails mediate chromatin stability and regulate gene expression. For this reason, it is important to understand structural dynamics of nucleosomes at atomic levels. We report a novel multiscale model of the fundamental chromatin unit, a nucleosome, using a simplified model for rapid discrete molecular dynamics simulations and an all-atom model for detailed structural investigation. Using a simplified structural model, we perform equilibrium simulations of a single nucleosome at various temperatures. We further reconstruct all-atom nucleosome structures from simulation trajectories. We find that histone tails bind to nucleosomal DNA via strong salt-bridge interactions over a wide range of temperatures, suggesting a mechanism of chromatin structural organization whereby histone tails regulate inter- and intranucleosomal assemblies via binding with nucleosomal DNA. We identify specific regions of the histone core H2A/H2B-H4/H3-H3/H4-H2B/H2A, termed "cold sites", which retain a significant fraction of contacts with adjoining residues throughout the simulation, indicating their functional role in nucleosome organization. Cold sites are clustered around H3-H3, H2A-H4 and H4-H2A interhistone interfaces, indicating the necessity of these contacts for nucleosome stability. Essential dynamics analysis of simulation trajectories shows that bending across the H3-H3 is a prominent mode of intranucleosomal dynamics. We postulate that effects of salts on mononucleosomes can be modeled in discrete molecular dynamics by modulating histone-DNA interaction potentials. Local fluctuations in nucleosomal DNA vary significantly along the DNA sequence, suggesting that only a fraction of histone-DNA contacts make strong interactions dominating mononucleosomal dynamics. Our findings suggest that histone tails have a direct functional role in stabilizing higher-order chromatin

  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. 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

  5. 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

  6. Predictive models of battle dynamics

    NASA Astrophysics Data System (ADS)

    Jelinek, Jan

    2001-09-01

    The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.

  7. 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.

  8. Nonlinear Dynamic Model Explains The Solar Dynamic

    NASA Astrophysics Data System (ADS)

    Kuman, Maria

    Nonlinear mathematical model in torus representation describes the solar dynamic. Its graphic presentation shows that without perturbing force the orbits of the planets would be circles; only perturbing force could elongate the circular orbits into ellipses. Since the Hubble telescope found that the planetary orbits of other stars in the Milky Way are also ellipses, powerful perturbing force must be present in our galaxy. Such perturbing force is the Sagittarius Dwarf Galaxy with its heavy Black Hole and leftover stars, which we see orbiting around the center of our galaxy. Since observations of NASA's SDO found that magnetic fields rule the solar activity, we can expect when the planets align and their magnetic moments sum up, the already perturbed stars to reverse their magnetic parity (represented graphically as periodic looping through the hole of the torus). We predict that planets aligned on both sides of the Sun, when their magnetic moments sum-up, would induce more flares in the turbulent equatorial zone, which would bulge. When planets align only on one side of the Sun, the strong magnetic gradient of their asymmetric pull would flip the magnetic poles of the Sun. The Sun would elongate pole-to-pole, emit some energy through the poles, and the solar activity would cease. Similar reshaping and emission was observed in stars called magnetars and experimentally observed in super-liquid fast-spinning Helium nanodroplets. We are certain that NASA's SDO will confirm our predictions.

  9. Dynamical Modelling of Meteoroid Streams

    NASA Astrophysics Data System (ADS)

    Clark, David; Wiegert, P. A.

    2012-10-01

    Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and

  10. Dynamic Model of Mesoscale Eddies

    NASA Astrophysics Data System (ADS)

    Dubovikov, Mikhail S.

    2003-04-01

    Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV

  11. An automated system for the analysis of G protein-coupled receptor transmembrane binding pockets: alignment, receptor-based pharmacophores, and their application.

    PubMed

    Kratochwil, Nicole A; Malherbe, Pari; Lindemann, Lothar; Ebeling, Martin; Hoener, Marius C; Mühlemann, Andreas; Porter, Richard H P; Stahl, Martin; Gerber, Paul R

    2005-01-01

    G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Here, a comprehensive and automated method allowing fast analysis and comparison of these putative binding pockets across the entire GPCR family is presented. The method relies on a robust alignment algorithm based on conservation indices, focusing on pharmacophore-like relationships between amino acids. Analysis of conservation patterns across the GPCR family and alignment to the rhodopsin X-ray structure allows the extraction of the amino acids lining the TM binding pocket in a so-called ligand binding pocket vector (LPV). In a second step, LPVs are translated to simple 3D receptor pharmacophore models, where each amino acid is represented by a single spherical pharmacophore feature and all atomic detail is omitted. Applications of the method include the assessment of selectivity issues, support of mutagenesis studies, and the derivation of rules for focused screening to identify chemical starting points in early drug discovery projects. Because of the coarseness of this 3D receptor pharmacophore model, however, meaningful scoring and ranking procedures of large sets of molecules are not justified. The LPV analysis of the trace amine-associated receptor family and its experimental validation is discussed as an example. The value of the 3D receptor model is demonstrated for a class C GPCR family, the metabotropic glutamate receptors.

  12. 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

  13. 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.

  14. Drug repositioning and pharmacophore identification in the discovery of hookworm MIF inhibitors.

    PubMed

    Cho, Yoonsang; Vermeire, Jon J; Merkel, Jane S; Leng, Lin; Du, Xin; Bucala, Richard; Cappello, Michael; Lolis, Elias

    2011-09-23

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

    PubMed Central

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

    2015-01-01

    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. PMID:25744369

  16. 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.

  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. 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.

  19. 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

  20. 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

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

    PubMed Central

    Cho, Yoonsang; Vermeire, Jon J.; Merkel, Jane S.; Leng, Lin; Du, Xin; Bucala, Richard; Cappello, Michael; Lolis, Elias

    2011-01-01

    SUMMARY 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. PMID:21944748

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Modeling wildfire incident complexity dynamics.

    PubMed

    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.

  7. 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

  8. Dynamical modelling of meteoroid streams

    NASA Astrophysics Data System (ADS)

    Clark, D. L.; Wiegert, P. A.

    2014-07-01

    Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis we are developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.

  9. Molecular modeling and molecular dynamics studies of hydralazine with human DNA methyltransferase 1.

    PubMed

    Singh, Narender; Dueñas-González, Alfonso; Lyko, Frank; Medina-Franco, Jose L

    2009-05-01

    DNA methyltransferases (DNMTs) are a family of enzymes that methylate DNA at the C5 position of cytosine residues, and their inhibition is a promising strategy for the treatment of various developmental and proliferative diseases, particularly cancers. In the present study, a binding model for hydralazine, with a validated homology model of human DNMT, was developed by the use of automated molecular docking and molecular dynamics simulations. The docking protocol was validated by predicting the binding mode of 2'-deoxycytidine, 5-azacytidine, and 5-aza-2'-deoxycytidine. The inhibitory activity of hydralazine toward DNMT may be rationalized at the molecular level by similar interactions within the binding pocket (e.g., by a similar pharmacophore) as established by substrate-like deoxycytidine analogues. These interactions involve a complex network of hydrogen bonds with arginine and glutamic acid residues that also play a major role in the mechanism of DNA methylation. Despite the different scaffolds of other non-nucleoside DNMT inhibitors such as procaine and procainamide, the current modeling work reveals that these drugs exhibit similar interactions within the DNMT1 binding site. These findings are valuable in guiding the rational design and virtual screening of novel DNMT inhibitors.

  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. PENG: a neural gas-based approach for pharmacophore elucidation. method design, validation, and virtual screening for novel ligands of LTA4H.

    PubMed

    Moser, Daniel; Wittmann, Sandra K; Kramer, Jan; Blöcher, René; Achenbach, Janosch; Pogoryelov, Denys; Proschak, Ewgenij

    2015-02-23

    The pharmacophore concept is commonly employed in virtual screening for hit identification. A pharmacophore is generally defined as the three-dimensional arrangement of the structural and physicochemical features of a compound responsible for its affinity to a pharmacological target. Given a number of active ligands binding to a particular target in the same manner, it can reasonably be assumed that they have some shared features, a common pharmacophore. We present a growing neural gas (GNG)-based approach for the extraction of the relevant features which we called PENG (pharmacophore elucidation by neural gas). Results of retrospective validation indicate an acceptable quality of the generated models. Additionally a prospective virtual screening for leukotriene A4 hydrolase (LTA4H) inhibitors was performed. LTA4H is a bifunctional zinc metalloprotease which displays both epoxide hydrolase and aminopeptidase activity. We could show that the PENG approach is able to predict the binding mode of the ligand by X-ray crystallography. Furthermore, we identified a novel chemotype of LTA4H inhibitors. PMID:25625859

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Characterizing and Modeling Citation Dynamics

    PubMed Central

    Eom, Young-Ho; Fortunato, Santo

    2011-01-01

    Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387

  17. 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.

  18. 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.

  19. 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.

  20. Dynamical Modeling of Mars' Paleoclimate

    NASA Technical Reports Server (NTRS)

    Richardson, Mark I.

    2004-01-01

    This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.

  1. 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.

  2. Synthesis and antihyperglycemic evaluation of new 2-hydrazolyl-4-thiazolidinone-5-carboxylic acids having pyrazolyl pharmacophores.

    PubMed

    Bhosle, Manisha R; Mali, Jyotirling R; Pal, Savita; Srivastava, Arvind K; Mane, Ramrao A

    2014-06-15

    In the search of new antihyperglycemic agents and following rational approach of drug designing here new 2-hydrazolyl-4-thiazolidinone-5-carboxylic acids (4a-g) with pyrazolyl pharmacophore have been synthesized via thia Michael addition reaction of 1-((3-(4-substituted phenyl)-1-phenyl-1H-pyrazol-4-yl)methylene)thiosemicarbazides (3a-g) with maleic anhydride. The required precursors, (3a-g) were obtained by condensing known 3-(4-substituted phenyl)-1-phenyl-1H-pyrazole-4-carbaldehydes (1a-g) with thiosemicarbazide in ethanol. The newly synthesized compounds (4a-g) have been evaluated for the antihyperglycemic activity in sucrose loaded rat model and among these compounds 4d, 4f and 4g have displayed significant antihyperglycemic activity.

  3. 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

  4. 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

  5. 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.

  6. Ultrafast de novo docking combining pharmacophores and combinatorics.

    PubMed

    Gastreich, Marcus; Lilienthal, Markus; Briem, Hans; Claussen, Holger

    2006-12-01

    We report on a successful de novo design approach which relies on the combination of multi-million compound combinatorial docking under receptor-based pharmacophore constraints. Inspired by a rationale by A.R. Leach et al., we document on the unification of two steps into one for ligand assembly. In the original work, fragments known to bind in protein active sites were connected forming novel ligand compounds by means of generic skeleton linkers and following a combinatorial approach. In our approach, the knowledge of fragments binding to the protein has been expressed in terms of a receptor-based pharmacophore definition. The combinatorial linking step is performed in situ during docking, starting from combinatorial libraries. Three sample scenarios growing in size and complexity (combinatorial libraries of 1 million, 1.3 million, and 22.4 million compounds) have been created to illustrate the method. Docking could be accomplished between minutes and several hours depending on the outset; the results were throughout promising. Technically, a module compatibility between FlexX(C) and FlexX-Pharm has been established. The background is explained, and the crucial points from an information scientist's perspective are highlighted.

  7. Floods and Societies: Dynamic Modeling

    NASA Astrophysics Data System (ADS)

    Di Baldassarre, G.; Viglione, A.; Carr, G.; Kuil, L., Jr.; Brandimarte, L.; Bloeschl, G.

    2014-12-01

    There is growing concern that future flood losses and fatalities might increase significantly in many regions of the world because of rapid urbanization in deltas and floodplains, in addition to sea level rise and climate change. To better anticipate long-term trajectories of future flood risk, there is a need to treat floodplains and deltas as fully coupled human-physical systems. Here we propose a novel approach to explore the long-term behavior emerging from the mutual interactions and feedbacks between physical and social systems. The implementation of our modeling framework shows that green societies, which cope with flooding by resettling out of floodplains, are more resilient to increasing flood frequency than technological societies, which deal with flooding by building levees. Also, we show that when coupled dynamics are accounted for, flood-poor periods could (paradoxically) be more dangerous than flood-rich periods.

  8. SSME structural dynamic model development

    NASA Technical Reports Server (NTRS)

    Foley, Michael J.

    1989-01-01

    The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

    PubMed

    Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

    2016-09-01

    The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria. PMID:27667641

  16. Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

    PubMed

    Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

    2016-09-01

    The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

  17. 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

  18. System Dynamics Models and Institutional Pricing Decisions.

    ERIC Educational Resources Information Center

    Chen, Fiona

    1986-01-01

    A system dynamics model for the pricing of tuition is presented, illustrating how such models enable decision-makers to anticipate cause-and-effect relationships and test alternative courses of action. (Author)

  19. Preliminary shuttle structural dynamics modeling design study

    NASA Technical Reports Server (NTRS)

    1972-01-01

    The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.

  20. 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.

  1. Comparative dynamics in a health investment model.

    PubMed

    Eisenring, C

    1999-10-01

    The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.

  2. 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

  3. 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.

  4. 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.

  5. 3D-Pharmacophore Mapping Using 4D-QSAR Analysis for the Cytotoxicity of Lamellarins Against Human Hormone-Dependent T47D Breast Cancer Cells

    PubMed Central

    Thipnate, Poonsiri; Liu, Jianzhong; Hannongbua, Supa; Hopfinger, A. J.

    2009-01-01

    4D-QSAR and 3D-pharmacophore models were built and investigated for the cytotoxicity using a training set of 25 lamellarins against human hormone dependent T47D breast cancer cells. Receptor-independent (RI) 4D-QSAR models were first constructed from the exploration of eight possible receptor binding alignments for the entire training set. Since the training set is small (25 compounds), the generality of the 4D-QSAR paradigm was then exploited to devise a strategy to maximize the extraction of binding information from the training set, and to also permit virtual screening of diverse lamellarin chemistry. 4D-QSAR models were sought for only six of the most potent lamellarins of the training set as well as another subset composed of lamellarins with constrained ranges in molecular weight and lipophilicty. This overall modeling strategy has permitted maximizing 3D-pharmacophore information from this small set of structurally complex lamellarins that can be used to drive future analog synthesis and the selection of alternate scaffolds. Overall, it was found that formation of an intermolecular hydrogen bond and hydrophobic interactions for substituents on the E ring most modulate the cytotoxicity against T47D breast cancer cells. Hydrophobic substitutions on the F-ring can also enhance cytotoxic potency. A complementary high throughput virtual screen to the 3D-pharmacophore models, a 4D-fingerprint QSAR model, was constructed using absolute molecular similarity. This 4D-fingerprint virtual high throughput screen permits a larger range of chemistry diversity to be assayed than the 4D-QSAR models. The optimized 4D-QSAR 3D-pharmacophore model has a LOO cross-correlation value of xv-r2 = 0.947, while the optimized 4D-fingerprint virtual screening model has a value of xv-r2 = 0.719. This work reveals that it is possible to develop significant QSAR, 3D-pharmacophore and virtual screening models for a small set of lamellarins showing cytotoxic behavior in breast cancer screens

  6. 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

  7. Opioid bifunctional ligands from morphine and the opioid pharmacophore Dmt-Tic.

    PubMed

    Balboni, Gianfranco; Salvadori, Severo; Marczak, Ewa D; Knapp, Brian I; Bidlack, Jean M; Lazarus, Lawrence H; Peng, Xuemei; Si, Yu Gui; Neumeyer, John L

    2011-02-01

    Bifunctional ligands containing an ester linkage between morphine and the δ-selective pharmacophore Dmt-Tic were synthesized, and their binding affinity and functional bioactivity at the μ, δ and κ opioid receptors determined. Bifunctional ligands containing or not a spacer of β-alanine between the two pharmacophores lose the μ agonism deriving from morphine becoming partial μ agonists 4 or μ antagonists 5. Partial κ agonism is evidenced only for compound 4. Finally, both compounds showed potent δ antagonism.

  8. A Separable Model for Dynamic Networks

    PubMed Central

    Krivitsky, Pavel N.; Handcock, Mark S.

    2013-01-01

    Summary Models of dynamic networks — networks that evolve over time — have manifold applications. We develop a discrete-time generative model for social network evolution that inherits the richness and flexibility of the class of exponential-family random graph models. The model — a Separable Temporal ERGM (STERGM) — facilitates separable modeling of the tie duration distributions and the structural dynamics of tie formation. We develop likelihood-based inference for the model, and provide computational algorithms for maximum likelihood estimation. We illustrate the interpretability of the model in analyzing a longitudinal network of friendship ties within a school. PMID:24443639

  9. Launch Vehicle Dynamics Demonstrator Model

    NASA Technical Reports Server (NTRS)

    1963-01-01

    The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control.

  10. 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.

  11. [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

  12. Stirling Convertor System Dynamic Model Developed

    NASA Technical Reports Server (NTRS)

    Lewandowski, Edward J.; Regan, Timothy F.

    2005-01-01

    Free-piston Stirling convertors are being developed for potential use on NASA exploration missions. In support of this effort, the NASA Glenn Research Center has developed the Stirling convertor System Dynamic Model (SDM). The SDM models the Stirling cycle thermodynamics; heat flow; gas, mechanical, and mounting dynamics; the linear alternator; and the controller. The SDM s scope extends from the thermal energy input to thermal, mechanical, and electrical energy output, allowing one to study complex system interactions among subsystems. Thermal, mechanical, fluid, magnetic, and electrical subsystems can be studied in one model. The SDM is a nonlinear time-domain model containing sub-cycle dynamics, which simulates transient and dynamic phenomena that other models cannot. The entire range of convertor operation is modeled, from startup to full-power conditions.

  13. 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

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

    PubMed

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

    2015-06-11

    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.

  15. Modelling Information System Dynamics: A Perspective.

    ERIC Educational Resources Information Center

    Oswitch, Pauline

    1983-01-01

    Describes British Library's work on Systems Dynamics, a set of techniques for building simulation models based on analysis of information feedback loops. Highlights include macro-simulation modelling activities of social science disciplines, systems analyses and models of information retrieval processes and library services, policy models, and…

  16. 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

  17. Nicotinic pharmacophore: the pyridine N of nicotine and carbonyl of acetylcholine hydrogen bond across a subunit interface to a backbone NH.

    PubMed

    Blum, Angela P; Lester, Henry A; Dougherty, Dennis A

    2010-07-27

    Pharmacophore models for nicotinic agonists have been proposed for four decades. Central to these models is the presence of a cationic nitrogen and a hydrogen bond acceptor. It is now well-established that the cationic center makes an important cation-pi interaction to a conserved tryptophan, but the donor to the proposed hydrogen bond acceptor has been more challenging to identify. A structure of nicotine bound to the acetylcholine binding protein predicted that the binding partner of the pharmacophore's second component was a water molecule, which also hydrogen bonds to the backbone of the complementary subunit of the receptors. Here we use unnatural amino acid mutagenesis coupled with agonist analogs to examine whether such a hydrogen bond is functionally significant in the alpha4beta2 neuronal nAChR, the receptor most associated with nicotine addiction. We find evidence for the hydrogen bond with the agonists nicotine, acetylcholine, carbamylcholine, and epibatidine. These data represent a completed nicotinic pharmacophore and offer insight into the design of new therapeutic agents that selectively target these receptors.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Dynamic phase transition in diluted Ising model

    NASA Astrophysics Data System (ADS)

    Chattopadhyay, Sourav; Gorai, Gopal; Santra, S. B.

    2015-06-01

    Dynamic phase transition in disordered Ising model in two dimensions has been studied in presence of external time dependent oscillating magnetic field applying Glauber Monte Carlo techniques. Dynamic phase transitions are identified estimating dynamic order parameter against temperature for different concentrations of disorder. For a given field strength and frequency for which there was no hysteresis, it is observed that disorder is able induce hysteresis in the system. Effect of increasing concentration of disorder on hysteresis loop area has also been studied.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Simple Dynamic Gasifier Model That Runs in Aspen Dynamics

    SciTech Connect

    Robinson, P.J.; Luyben, W.L.

    2008-10-15

    Gasification (or partial oxidation) is a vital component of 'clean coal' technology. Sulfur and nitrogen emissions can be reduced, overall energy efficiency is increased, and carbon dioxide recovery and sequestration are facilitated. Gasification units in an electric power generation plant produce a fuel for driving combustion turbines. Gasification units in a chemical plant generate gas, which can be used to produce a wide spectrum of chemical products. Future plants are predicted to be hybrid power/chemical plants with gasification as the key unit operation. The widely used process simulator Aspen Plus provides a library of models that can be used to develop an overall gasifier model that handles solids. So steady-state design and optimization studies of processes with gasifiers can be undertaken. This paper presents a simple approximate method for achieving the objective of having a gasifier model that can be exported into Aspen Dynamics. The basic idea is to use a high molecular weight hydrocarbon that is present in the Aspen library as a pseudofuel. This component should have the same 1:1 hydrogen-to-carbon ratio that is found in coal and biomass. For many plantwide dynamic studies, a rigorous high-fidelity dynamic model of the gasifier is not needed because its dynamics are very fast and the gasifier gas volume is a relatively small fraction of the total volume of the entire plant. The proposed approximate model captures the essential macroscale thermal, flow, composition, and pressure dynamics. This paper does not attempt to optimize the design or control of gasifiers but merely presents an idea of how to dynamically simulate coal gasification in an approximate way.

  9. 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

  10. Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

    PubMed Central

    Chen, Zhi; Li, Hong-lin; Zhang, Qi-jun; Bao, Xiao-guang; Yu, Kun-qian; Luo, Xiao-min; Zhu, Wei-liang; Jiang, Hua-liang

    2009-01-01

    Aim: This study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods. Methods: All virtual screens were performed on two data sets of small molecules with both actives and decoys against eight structurally diverse protein targets, namely angiotensin converting enzyme (ACE), acetylcholinesterase (AChE), androgen receptor (AR), D-alanyl-D-alanine carboxypeptidase (DacA), dihydrofolate reductase (DHFR), estrogen receptors α (ERα), HIV-1 protease (HIV-pr), and thymidine kinase (TK). Each pharmacophore model was constructed based on several X-ray structures of protein-ligand complexes. Virtual screens were performed using four screening standards, the program Catalyst for PBVS and three docking programs (DOCK, GOLD and Glide) for DBVS. Results: Of the sixteen sets of virtual screens (one target versus two testing databases), the enrichment factors of fourteen cases using the PBVS method were higher than those using DBVS methods. The average hit rates over the eight targets at 2% and 5% of the highest ranks of the entire databases for PBVS are much higher than those for DBVS. Conclusion: The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery. PMID:19935678

  11. Inhibitors of human tyrosyl-DNA phospodiesterase (hTdp1) developed by virtual screening using ligand-based pharmacophores.

    PubMed

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

    2010-01-01

    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). A total of 46 compounds matching the three-dimensional arrangement of the pharmacophoric features were assayed. Using a high-throughput screening assay, we have identified an 1H-indol-3-yl-acetic acid derivative as a potent Tdp1 inhibitor with an IC(50) value of 7.94 microM. The obtained novel chemotype may provide a new scaffold for developing inhibitors of Tdp1. PMID:19963390

  12. 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

  13. Airship dynamics modeling: A literature review

    NASA Astrophysics Data System (ADS)

    Li, Yuwen; Nahon, Meyer; Sharf, Inna

    2011-04-01

    The resurgence of airships has created a need for dynamics models and simulation capabilities adapted to these lighter-than-air vehicles. However, the modeling techniques for airship dynamics have lagged behind and are less systematic than those for fixed-wing aircraft. A state-of-the-art literature review is presented on airship dynamics modeling, aiming to provide a comprehensive description of the main problems in this area and a useful source of references for researchers and engineers interested in modern airship applications. The references are categorized according to the major topics in this area: aerodynamics, flight dynamics, incorporation of structural flexibility, incorporation of atmospheric turbulence, and effects of ballonets. Relevant analytical, numerical, and semi-empirical techniques are discussed, with a particular focus on how the main differences between lighter-than-air and heavier-than-air aircraft have been addressed in the modeling. Directions are suggested for future research on each of these topics.

  14. 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.

  15. 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

  16. The Higher Moments Dynamic on SIS Model

    NASA Astrophysics Data System (ADS)

    Pinto, Alberto; Martins, José; Stollenwerk, Nico

    2009-09-01

    The basic contact process or the SIS model is a well known epidemic process and have been studied for a wide class of people. In an epidemiological context, many authors worked on the SIS model considering only the dynamic of the first moments of infecteds, i.e., the mean value and the variance of the infected individuals. In this work, we study not only the dynamic of the first moments of infecteds but also on the dynamic of the higher moments. Recursively, we consider the dynamic equations for all the moments of infecteds and, applying the moment closure approximation, we obtain the stationary states of the state variables. We observe that the stationary states of the SIS model, in the moment closure approximation, can be used to obtain good approximations of the quasi-stationary states of the SIS model.

  17. MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

    PubMed Central

    CHAHINE, Georges L.; HSIAO, Chao-Tsung

    2012-01-01

    Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Dynamic process modeling with recurrent neural networks

    SciTech Connect

    You, Yong; Nikolaou, M. . Dept. of Chemical Engineering)

    1993-10-01

    Mathematical models play an important role in control system synthesis. However, due to the inherent nonlinearity, complexity and uncertainty of chemical processes, it is usually difficult to obtain an accurate model for a chemical engineering system. A method of nonlinear static and dynamic process modeling via recurrent neural networks (RNNs) is studied. An RNN model is a set of coupled nonlinear ordinary differential equations in continuous time domain with nonlinear dynamic node characteristics as well as both feed forward and feedback connections. For such networks, each physical input to a system corresponds to exactly one input to the network. The system's dynamics are captured by the internal structure of the network. The structure of RNN models may be more natural and attractive than that of feed forward neural network models, but computation time for training is longer. Simulation results show that RNNs can learn both steady-state relationships and process dynamics of continuous and batch, single-input/single-output and multi-input/multi-output systems in a simple and direct manner. Training of RNNs shows only small degradation in the presence of noise in the training data. Thus, RNNs constitute a feasible alternative to layered feed forward back propagation neural networks in steady-state and dynamic process modeling and model-based control.

  3. 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.

  4. Model systems for single molecule polymer dynamics

    PubMed Central

    Latinwo, Folarin

    2012-01-01

    Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980

  5. 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.

  6. A stochastic model of human gait dynamics

    NASA Astrophysics Data System (ADS)

    Ashkenazy, Yosef; M. Hausdorff, Jeffrey; Ch. Ivanov, Plamen; Eugene Stanley, H.

    2002-12-01

    We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood-including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.

  7. The future dynamic world model

    NASA Astrophysics Data System (ADS)

    Karr, Thomas J.

    2014-10-01

    Defense and security forces exploit sensor data by means of a model of the world. They use a world model to geolocate sensor data, fuse it with other data, navigate platforms, recognize features and feature changes, etc. However, their need for situational awareness today exceeds the capabilities of their current world model for defense operations, despite the great advances of sensing technology in recent decades. I review emerging technologies that may enable a great improvement in the spatial and spectral coverage, the timeliness, and the functional insight of their world model.

  8. 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].

  9. 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.

  10. 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.

  11. 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.

  12. Modeling cell shape and dynamics on micropatterns

    PubMed Central

    Albert, Philipp J.; Schwarz, Ulrich S.

    2016-01-01

    ABSTRACT Adhesive micropatterns have become a standard tool to study cells under defined conditions. Applications range from controlling the differentiation and fate of single cells to guiding the collective migration of cell sheets. In long-term experiments, single cell normalization is challenged by cell division. For all of these setups, mathematical models predicting cell shape and dynamics can guide pattern design. Here we review recent advances in predicting and explaining cell shape, traction forces and dynamics on micropatterns. Starting with contour models as the simplest approach to explain concave cell shapes, we move on to network and continuum descriptions as examples for static models. To describe dynamic processes, cellular Potts, vertex and phase field models can be used. Different types of model are appropriate to address different biological questions and together, they provide a versatile tool box to predict cell behavior on micropatterns. PMID:26838278

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Dynamic causal modeling with genetic algorithms.

    PubMed

    Pyka, M; Heider, D; Hauke, S; Kircher, T; Jansen, A

    2011-01-15

    In the last years, dynamic causal modeling has gained increased popularity in the neuroimaging community as an approach for the estimation of effective connectivity from functional magnetic resonance imaging (fMRI) data. The algorithm calls for an a priori defined model, whose parameter estimates are subsequently computed upon the given data. As the number of possible models increases exponentially with additional areas, it rapidly becomes inefficient to compute parameter estimates for all models in order to reveal the family of models with the highest posterior probability. In the present study, we developed a genetic algorithm for dynamic causal models and investigated whether this evolutionary approach can accelerate the model search. In this context, the configuration of the intrinsic, extrinsic and bilinear connection matrices represents the genetic code and Bayesian model selection serves as a fitness function. Using crossover and mutation, populations of models are created and compared with each other. The most probable ones survive the current generation and serve as a source for the next generation of models. Tests with artificially created data sets show that the genetic algorithm approximates the most plausible models faster than a random-driven brute-force search. The fitness landscape revealed by the genetic algorithm indicates that dynamic causal modeling has excellent properties for evolution-driven optimization techniques.

  18. 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.

  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. Cellular automata modeling of pedestrian's crossing dynamics.

    PubMed

    Zhang, Jin; Wang, Hui; Li, Ping

    2004-07-01

    Cellular automata modeling techniques and the characteristics of mixed traffic flow were used to derive the 2-dimensional model presented here for simulation of pedestrian's crossing dynamics. A conception of "stop point" is introduced to deal with traffic obstacles and resolve conflicts among pedestrians or between pedestrians and the other vehicles on the crosswalk. The model can be easily extended, is very efficient for simulation of pedestrian's crossing dynamics, can be integrated into traffic simulation software, and has been proved feasible by simulation experiments.

  1. A dynamical model for the Utricularia trap.

    PubMed

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

    2012-11-01

    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. 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.

  3. 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.

  4. 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

  5. Dispersive models describing mosquitoes’ population dynamics

    NASA Astrophysics Data System (ADS)

    Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

    2016-08-01

    The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

  6. 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.

  7. Alternative models for cyclic lemming dynamics.

    PubMed

    Wang, Hao; Kuang, Yang

    2007-01-01

    Many natural population growths and interactions are affected by seasonal changes, suggesting that these natural population dynamics should be modeled by nonautonomous differential equations instead of autonomous differential equations. Through a series of carefully derived models of the well documented high-amplitude, large-period fluctuations of lemming populations, we argue that when appropriately formulated, autonomous differential equations may capture much of the desirable rich dynamics, such as the existence of a periodic solution with period and amplitude close to that of approximately periodic solutions produced by the more natural but mathematically daunt ing nonautonomous models. We start this series of models from the Barrow model, a well formulated model for the dynamics of food-lemming interaction at Point Barrow (Alaska, USA) with sufficient experimental data. Our work suggests that an autonomous system can indeed be a good approximation to the moss-lemming dynamics at Point Barrow. This, together with our bifurcation analysis, indicates that neither seasonal factors (expressed by time dependent moss growth rate and lemming death rate in the Barrow model) nor the moss growth rate and lemming death rate are the main culprits of the observed multi-year lemming cycles. We suspect that the main culprits may include high lemming predation rate, high lemming birth rate, and low lemming self-limitation rate.

  8. Error dynamics in shell models for turbulence

    NASA Astrophysics Data System (ADS)

    De Cruz, Lesley; Vannitsem, Stéphane

    2013-04-01

    A deep understanding of the error dynamics in turbulent systems is crucial to estimate the horizon of predictability, and to quantify the impact of initial-condition (IC) and model errors on the statistical characteristics of ensemble prediction systems. We present a study of the dynamics of combined IC and model errors in a turbulent system. We use the Sabra shell model [1], a spectral model which captures the characteristic properties of a turbulent system using a low number of variables (of the order of 50). The analytical properties of the short-term error dynamics in the Sabra shell model are investigated using the methodology described in Ref. [2], and compared to numerical results. Of particular interest is the property of a dissipative system that the mean squared error (MSE) reaches a minimum shortly after the introduction of an IC error. The distribution of the minimum-error times is investigated, and the spatial-scale dependence of the error dynamics is discussed. At longer time scales, our simulations confirm the well-known fact that an arbitrarily small error in the initial conditions contaminates the integral scale in a time that is independent of the scale of the initial error. Finally, we report on the error dynamics in the presence of a crossover between 3D and 2D turbulence, known to characterise the atmosphere. References [1] V. S. L'vov, E. Podivilov, A. Pomyalov, I. Procaccia, and D. Vandembroucq. Improved shell model of turbulence. Physical Review E, 58:1811-1822, August 1998. [2] C. Nicolis, R. A. P. Perdigao, and S. Vannitsem. Dynamics of Prediction Errors under the Combined Effect of Initial Condition and Model Errors. Journal of Atmospheric Sciences, 66:766, 2009.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. Dynamic modeling of solar dynamic components and systems

    NASA Astrophysics Data System (ADS)

    Hochstein, John 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. A Monodisperse Aerosol Dynamics Model Mono32

    NASA Astrophysics Data System (ADS)

    Pirjola, L.

    A recently developed aerosol dynamics model MONO32 (and MULTIMONO) (Pir- jola and Kulmala, 2000) is a Lagrangian type box model which uses mondisperse representation for particle size distribution. The model takes into account gas-phase chemistry and aerosol dynamics including emissions and dry deposition of gases and particles, chemical reactions in the gas phase, homogeneous binary H2SO4-H2O or ternary H2SO4-H2O-NH3 nucleation, multicomponent condensation of H2SO4, H2O, HNO3, NH3 and some organic vapour onto particles as well as inter- and in- tramode coagulation of particles. Particles can consist of soluble material such as sul- phate, nitrate, ammonium, sodium cloride, as well as insoluble material such as or- ganic carbon, elemental carbon and mineral dust. Hygroscopic properties and growth of particles were studied by the model. Simulations predicted that nucleation mode particles grew with a growth rate of 2.5-3 nm/h if the source rate of a condensable nonvolatile organic vapour exceeded 10^5 cm^-3 s^-1 and the condensation sink of the pre-existing particles was 0.9x10^-3 s^-1. These results are in good agreemnet with the measurements in Southern Finland. Further, these particles are able to grow to CCN sizes, thus affecting climate. The model was compared very well with the sectional model AEROFOR2 (Pirjola and Kulmala, 2001). It is physically sound and computa- tionally efficient model also for using as a module for regional transport models. Pirjola, L. and Kulmala, M. (2000) Aerosol dynamical model MULTIMONO, Boreal research 5, 361-372. Pirjola, L. and Kulmala, M. (2001) Development of particle size and composition distribution with aerosol dynamics model AEROFOR2. Tellus 53B, 491-509. Pirjola, L., Korhonen, H. and Kulmala, M. (2002) Condensation/ evaporation of insoluble organic vapour as functions of source rate and saturation vapour pressure. J. Geophys. Res. (in press).

  4. Validation of potential inhibitors for SrtA against Bacillus anthracis by combined approach of ligand-based and molecular dynamics simulation.

    PubMed

    Selvaraj, Chandrabose; Singh, Sanjeev Kumar

    2014-01-01

    The development of SrtA inhibitors targeting the biothreat organism namely Bacillus anthracis was achieved by the combined approach of pharmacophore modeling, binding interactions, electron transferring capacity, ADME, and Molecular dynamics studies. In this study, experimentally reported Ba-SrtA inhibitors (pyridazinone and pyrazolethione derivatives) were considered for the development of enhanced pharmacophoric model. The obtained AAAHR hypothesis was a pure theoretical concept that accounts for common molecular interaction network present in experimentally active pyridazinone and pyrazolethione derivatives. Pharmacophore-based screening of AAAHR hypothesis provides several new compounds, and those compounds were treated with four phases of docking protocols with combined Glide-QPLD docking approach. In this approach, scoring and charge accuracy variations were seen to be dominated by QM/MM approach through the allocation of partial charges. Finally, we reported the best compounds from binding db, Chembridge db, and Toslab based on scoring values, energy parameters, electron transfer reaction, ADME, and cell adhesion inhibition activity. The dynamic state of interaction and binding energy assess that new compounds are more active inside the binding pocket and these compounds on experimental validations will survive as better inhibitors for targeting the cell adhesion mechanism of Ba-SrtA. PMID:23869520

  5. Opioid Bifunctional Ligands from Morphine and the Opioid Pharmacophore Dmt-Tic

    PubMed Central

    Balboni, Gianfranco; Salvadori, Severo; Marczak, Ewa D.; Knapp, Brian I.; Bidlack, Jean M.; Lazarus, Lawrence H.; Peng, Xuemei; Si, Yu Gui; Neumeyer, John L.

    2010-01-01

    Bifunctional ligands containing an ester linkage between morphine and the δ-selective pharmacophore Dmt-Tic were synthesized, and their binding affinity and functional bioactivity at the μ, δ and κ opioid receptors determined. Bifunctional ligands containing or not a spacer of β-alanine between the two pharmacophores lose the μ agonism deriving from morphine becoming partial μ agonists 4 or μ antagonists 5. Partial κ agonism is evidenced only for compound 4. Finally, both compounds showed potent δ antagonism. PMID:21216504

  6. Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist.

    PubMed

    Cho, Nam-Chul; Seo, Seoung-Hwan; Kim, Dohee; Shin, Ji-Sun; Ju, Jeongmin; Seong, Jihye; Seo, Seon Hee; Lee, Iiyoun; Lee, Kyung-Tae; Kim, Yun Kyung; No, Kyoung Tai; Pae, Ae Nim

    2016-08-01

    Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe243(5.39) is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na(+) allosteric site in contrast to PAR2 agonist that showed Na(+) relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands. PMID:27600555

  7. 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

  8. 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

  9. Modeling share dynamics by extracting competition structure

    NASA Astrophysics Data System (ADS)

    Kimura, Masahiro; Saito, Kazumi; Ueda, Naonori

    2004-11-01

    We propose a new method for analyzing multivariate time-series data governed by competitive dynamics such as fluctuations in the number of visitors to Web sites that form a market. To achieve this aim, we construct a probabilistic dynamical model using a replicator equation and derive its learning algorithm. This method is implemented for both categorizing the sites into groups of competitors and predicting the future shares of the sites based on the observed time-series data. We confirmed experimentally, using synthetic data, that the method successfully identifies the true model structure, and exhibits better prediction performance than conventional methods that leave competitive dynamics out of consideration. We also experimentally demonstrated, using real data of visitors to 20 Web sites offering streaming video contents, that the method suggested a reasonable competition structure that conventional methods failed to find and that it outperformed them in terms of predictive performance.

  10. 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.

  11. 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.

  12. Modeling of Reactor Kinetics and Dynamics

    SciTech Connect

    Matthew Johnson; Scott Lucas; Pavel Tsvetkov

    2010-09-01

    In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.

  13. Developmental Stages in Dynamic Plant Growth Models

    NASA Astrophysics Data System (ADS)

    Maclean, Heather; Dochain, Denis; Waters, Geoff; Stasiak, Michael; Dixon, Mike; Van Der Straeten, Dominique

    2011-09-01

    During the growth of red beet plants in a closed environment plant growth chamber, a change in metabolism was observed (decreasing photosynthetic quotient) which was not predicted by a previously developed simple dynamic model of photosynthesis and respiration reactions. The incorporation of developmental stages into the model allowed for the representation of this change in metabolism without adding unnecessary complexity. Developmental stages were implemented by dividing the model into two successive sub-models with independent yields. The transition between the phases was detected based on online measurements. Results showed an accurate prediction of carbon dioxide and oxygen fluxes.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. Dynamic modeling and simulation of planetary rovers

    NASA Astrophysics Data System (ADS)

    Lindemann, Randel A.

    1992-02-01

    This paper documents a preliminary study into the dynamic modeling and computer simulation of wheeled surface vehicles. The research centered on the feasibility of using commercially available multibody dynamics codes running on engineering workstations to perform the analysis. The results indicated that physically representative vehicle mechanics can be modeled and simulated in state-of-the-art Computer Aided Engineering environments, but at excessive cost in modeling and computation time. The results lead to the recommendation for the development of an efficient rover mobility-specific software system. This system would be used for vehicle design and simulation in planetary environments; controls prototyping, design, and testing; as well as local navigation simulation and expectation planning.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  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. 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.

  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. 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.

  18. New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies.

    PubMed

    Patel, Dhilon S; Bharatam, Prasad V

    2006-01-01

    Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski's rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.

  19. Five challenges in modelling interacting strain dynamics.

    PubMed

    Wikramaratna, Paul S; Kucharski, Adam; Gupta, Sunetra; Andreasen, Viggo; McLean, Angela R; Gog, Julia R

    2015-03-01

    Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called "strain space". We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures.

  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. Identification of the Pharmacophore of the CC Chemokine-binding Proteins Evasin-1 and -4 Using Phage Display*

    PubMed Central

    Bonvin, Pauline; Dunn, Steven M.; Rousseau, François; Dyer, Douglas P.; Shaw, Jeffrey; Power, Christine A.; Handel, Tracy M.; Proudfoot, Amanda E. I.

    2014-01-01

    To elucidate the ligand-binding surface of the CC chemokine-binding proteins Evasin-1 and Evasin-4, produced by the tick Rhipicephalus sanguineus, we sought to identify the key determinants responsible for their different chemokine selectivities by expressing Evasin mutants using phage display. We first designed alanine mutants based on the Evasin-1·CCL3 complex structure and an in silico model of Evasin-4 bound to CCL3. The mutants were displayed on M13 phage particles, and binding to chemokine was assessed by ELISA. Selected variants were then produced as purified proteins and characterized by surface plasmon resonance analysis and inhibition of chemotaxis. The method was validated by confirming the importance of Phe-14 and Trp-89 to the inhibitory properties of Evasin-1 and led to the identification of a third crucial residue, Asn-88. Two amino acids, Glu-16 and Tyr-19, were identified as key residues for binding and inhibition of Evasin-4. In a parallel approach, we identified one clone (Y28Q/N60D) that showed a clear reduction in binding to CCL3, CCL5, and CCL8. It therefore appears that Evasin-1 and -4 use different pharmacophores to bind CC chemokines, with the principal binding occurring through the C terminus of Evasin-1, but through the N-terminal region of Evasin-4. However, both proteins appear to target chemokine N termini, presumably because these domains are key to receptor signaling. The results also suggest that phage display may offer a useful approach for rapid investigation of the pharmacophores of small inhibitory binding proteins. PMID:25266725

  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. Dynamic Alignment Models for Neural Coding

    PubMed Central

    Kollmorgen, Sepp; Hahnloser, Richard H. R.

    2014-01-01

    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

  4. Interval modeling of dynamics for multibody systems

    NASA Astrophysics Data System (ADS)

    Auer, Ekaterina

    2007-02-01

    Modeling of multibody systems is an important though demanding field of application for interval arithmetic. Interval modeling of dynamics is particularly challenging, not least because of the differential equations which have to be solved in the process. Most modeling tools transform these equations into a (non-autonomous) initial value problem, interval algorithms for solving of which are known. The challenge then consists in finding interfaces between these algorithms and the modeling tools. This includes choosing between "symbolic" and "numerical" modeling environments, transforming the usually non-autonomous resulting system into an autonomous one, ensuring conformity of the new interval version to the old numerical, etc. In this paper, we focus on modeling multibody systems' dynamics with the interval extension of the "numerical" environment MOBILE, discuss the techniques which make the uniform treatment of interval and non-interval modeling easier, comment on the wrapping effect, and give reasons for our choice of MOBILE by comparing the results achieved with its help with those obtained by analogous symbolic tools.

  5. 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

  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. Modeling the dynamic characteristics of pneumatic muscle.

    PubMed

    Reynolds, D B; Repperger, D W; Phillips, C A; Bandry, G

    2003-03-01

    A pneumatic muscle (PM) system was studied to determine whether a three-element model could describe its dynamics. As far as the authors are aware, this model has not been used to describe the dynamics of PM. A new phenomenological model consists of a contractile (force-generating) element, spring element, and damping element in parallel. The PM system was investigated using an apparatus that allowed precise and accurate actuation pressure (P) control by a linear servo-valve. Length change of the PM was measured by a linear potentiometer. Spring and damping element functions of P were determined by a static perturbation method at several constant P values. These results indicate that at constant P, PM behaves as a spring and damper in parallel. The contractile element function of P was determined by the response to a step input in P, using values of spring and damping elements from the perturbation study. The study showed that the resulting coefficient functions of the three-element model describe the dynamic response to the step input of P accurately, indicating that the static perturbation results can be applied to the dynamic case. This model is further validated by accurately predicting the contraction response to a triangular P waveform. All three elements have pressure-dependent coefficients for pressure P in the range 207 < or = P < or = 621 kPa (30 < or = P < or = 90 psi). Studies with a step decrease in P (relaxation of the PM) indicate that the damping element coefficient is smaller during relaxation than contraction.

  8. 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

  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. 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.

  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. 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.

  13. Dynamic mesh for TCAD modeling with ECORCE

    NASA Astrophysics Data System (ADS)

    Michez, A.; Boch, J.; Touboul, A.; Saigné, F.

    2016-08-01

    Mesh generation for TCAD modeling is challenging. Because densities of carriers can change by several orders of magnitude in thin areas, a significant change of the solution can be observed for two very similar meshes. The mesh must be defined at best to minimize this change. To address this issue, a criterion based on polynomial interpolation on adjacent nodes is proposed that adjusts accurately the mesh to the gradients of Degrees of Freedom. Furthermore, a dynamic mesh that follows changes of DF in DC and transient mode is a powerful tool for TCAD users. But, in transient modeling, adding nodes to a mesh induces oscillations in the solution that appears as spikes at the current collected at the contacts. This paper proposes two schemes that solve this problem. Examples show that using these techniques, the dynamic mesh generator of the TCAD tool ECORCE handle semiconductors devices in DC and transient mode.

  14. Modeling of dynamic fragmentation in brittle materials

    NASA Astrophysics Data System (ADS)

    Miller, Olga

    Fragmentation of brittle materials under high rates of loading is commonly encountered in materials processing and under impact loading conditions. Theoretical models intended to correlate the features of dynamic fragmentation have been suggested during the past few years with the goal of providing a rational basis for prediction of fragment sizes. In this thesis, a new model based on the dynamics of the process is developed. In this model, the spatial distribution and strength variation representative of flaws in real brittle materials are taken into account. The model captures the competition between rising mean stress in a brittle material due to an imposed high strain rate and falling mean stress due to loss of compliance. The model is studied computationally through an adaptation of a concept introduced by Xu and Needleman (1994). The deformable body is first divided into many small regions. Then, the mechanical behavior of the material is characterized by two constitutive relations, a volumetric constitutive relationship between stress and strain within the small continuous regions and a cohesive surface constitutive relationship between traction and displacement discontinuity across the cohesive surfaces between the small regions. These surfaces provide prospective fracture paths. Numerical experiments were conducted for a system with initial and boundary conditions similar to those invoked in the simple energy balance models, in order to provide a basis for comparison. It is found that, these models lead to estimates of fragment size which are an order of magnitude larger than those obtained by a more detailed calculation. The differences indicate that the simple analytical models, which deal with the onset of fragmentation but not its evolution, are inadequate as a basis for a complete description of a dynamic fragmentation process. The computational model is then adapted to interpret experimental observations on the increasing energy dissipation for

  15. A Model for Nonstationary Market Dynamics with Nontrivial Dynamical Scaling

    NASA Astrophysics Data System (ADS)

    Liu, Min; Bassler, Kevin E.

    2008-03-01

    In a recent empirical analysis of the Euro/Dollar exchange rate [Bassler, et al., PNAS 104, 17287 (2007)] it was found that during certain periods of the day the market returns scale with Hurst exponents H that are significantly different from 1/2. In some of these periods it is less than 1/2, while in others it is greater than 1/2. In this talk we will propose a possible origin for this behavior and other stylized market facts, including short time negative autocorrelations of returns, in terms of a nonstationary compound Poisson process with a time-dependent intensity rate function that results from a changing bid-ask spread in the microscopic market. The model correctly describes the dynamic scaling behavior of a simple reaction-diffusion model of a limit-order book. That model, like the Euro/Dollar exchange rate, has nonstationary return increments and a Hurst exponent H not equal to 1/2.

  16. 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.

  17. 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

  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. Pharmacophore and 3D-QSAR characterization of 6-arylquinazolin-4-amines as Cdc2-like kinase 4 (Clk4) and dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) inhibitors.

    PubMed

    Pan, Yongmei; Wang, Yanli; Bryant, Stephen H

    2013-04-22

    Cdc2-like kinase 4 (Clk4) and dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) are protein kinases that are promising targets for treatment of diseases caused by abnormal gene splicing. 6-Arylquinazolin-4-amines have been recently identified as potent Clk4 and Dyrk1A inhibitors. In order to understand the structure-activity correlation of these analogs, we have applied ligand-based pharmacophore and 3D-QSAR modeling combined with structure-based homology modeling and docking. The high R(2) and Q(2) (0.88 and 0.79 for Clk4, 0.85 and 0.82 for Dyrk1A, respectively) based on validation with training and test set compounds suggested that the generated 3D-QSAR models are reliable in predicting novel ligand activities against Clk4 and Dyrk1A. The binding mode identified through docking ligands to the ATP binding domain of Clk4 was consistent with the structural properties and energy field contour maps characterized by pharmacophore and 3D-QSAR models and gave valuable insights into the structure-activity profile of 6-arylquinazolin-4-amine analogs. The obtained 3D-QSAR and pharmacophore models in combination with the binding mode between inhibitor and residues of Clk4 will be helpful for future lead compound identification and optimization to design potent and selective Clk4 and Dyrk1A inhibitors. PMID:23496085

  20. 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.

  1. Dynamical model of birdsong maintenance and control

    NASA Astrophysics Data System (ADS)

    Abarbanel, Henry D. I.; Talathi, Sachin S.; Mindlin, Gabriel; Rabinovich, Misha; Gibb, Leif

    2004-11-01

    The neuroethology of song learning, production, and maintenance in songbirds presents interesting similarities to human speech. We have developed a biophysical model of the manner in which song could be maintained in adult songbirds. This model may inform us about the human counterpart to these processes. In songbirds, signals generated in nucleus High Vocal center (HVc) follow a direct route along a premotor pathway to the robust nucleus of the archistriatum (RA) as well as an indirect route to RA through the anterior forebrain pathway (AFP): the neurons of RA are innervated from both sources. HVc expresses very sparse bursts of spikes having interspike intervals of about 2ms . The expressions of these bursts arrive at the RA with a time difference ΔT≈50±10ms between the two pathways. The observed combination of AMPA and NMDA receptors at RA projection neurons suggests that long-term potentiation and long-term depression can both be induced by spike timing plasticity through the pairing of the HVc and AFP signals. We present a dynamical model that stabilizes this synaptic plasticity through a feedback from the RA to the AFP using known connections. The stabilization occurs dynamically and is absent when the RA→AFP connection is removed. This requires a dynamical selection of ΔT . The model does this, and ΔT lies within the observed range. Our model represents an illustration of a functional consequence of activity-dependent plasticity directly connected with neuroethological observations. Within the model the parameters of the AFP, and thus the magnitude of ΔT , can also be tuned to an unstable regime. This means that destabilization might be induced by neuromodulation of the AFP.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. Dynamic Factor Analysis Models with Time-Varying Parameters

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-01-01

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor model…

  7. Dynamic model of Earth's radiation belts

    NASA Astrophysics Data System (ADS)

    Matsumoto, Haruhisa; Koshiishi, Hideki; Goka, Tateo; Obara, Takahiro

    The radiation belts are the region that energetic charged particles are trapped by Earth's magnetic field. It is well known that the energetic particle flux vary during geomagnetic distur-bances, and, the relativistic electrons in the outer radiation belt change with solar wind speed. Many researches have been studied about the flux variation of radiation belt, but the mecha-nism of the variation has not been understood in detail. We have developed a new dynamic model of energetic particles trapped in the based on the data from the MDS-1 spacecraft. This model reproduces the dynamic of radiation belt by running average using magnetic activity index(AP) and running average solar wind speed. This model covers the energy ranges of 0.4-2MeV for electrons, 0.9-210 MeV for protons, and 6-140 MeV for helium ions, and it is valid from low altitudes (approximately 500km) to geosynchronous orbit altitude. We discuss the advantage of the new model, and comparisons between MDS-1 data and our new model.

  8. 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

  9. Implementation of pseudoreceptor-based pharmacophore queries in the prediction of probable protein targets: explorations in the protein structural profile of Zea mays.

    PubMed

    Kumar, Sivakumar Prasanth; Jha, Prakash C; Pandya, Himanshu A; Jasrai, Yogesh T

    2014-07-01

    Molecular docking plays an important role in the protein target identification by prioritizing probable druggable proteins using docking energies. Due to the limitations of docking scoring schemes, there arises a need for structure-based approaches to acquire confidence in theoretical binding affinities. In this direction, we present here a receptor (protein)-based approach to predict probable protein targets using a small molecule of interest. We adopted a reverse approach wherein the ligand pharmacophore features were used to decipher interaction complementary amino acids of protein cavities (a pseudoreceptor) and expressed as queries to match the cavities or binding sites of the protein dataset. These pseudoreceptor-based pharmacophore queries were used to estimate total probabilities of each protein cavity thereby representing the ligand binding efficiency of the protein. We applied this approach to predict 3 experimental protein targets among 28 Zea mays structural data using 3 co-crystallized ligands as inputs and compared its effectiveness using conventional docking results. We suggest that the combination of total probabilities and docking energies increases the confidence in prioritizing probable protein targets using docking methods. These prediction hypotheses were further supported by DrugScoreX (DSX) pair potential calculations and molecular dynamic simulations. PMID:24756543

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Modeling HIF relevant longitudinal dynamics in UMER

    NASA Astrophysics Data System (ADS)

    Beaudoin, B. L.; Bernal, S.; Blanco, C.; Haber, I.; Kishek, R. A.; Koeth, T.; Mo, Y.

    2014-01-01

    The foremost challenge for Heavy-Ion Fusion (HIF) is achieving sufficiently low emittances and small energy spreads in the presence of intense space-charge, to achieve the high deposition densities necessary for pellet ignition. The University of Maryland Electron Ring (UMER) uses intense low-energy electron beams to access the scaled physics of HIF drivers. In particular, the long path-length propagation in UMER presents an opportunity to study, at realistic scales, the longitudinal beam dynamics and manipulations required for such a driver. With the use of induction modules, as in the ion machines such as NDCX-II, the resulting bunch dynamics show evidence of space-charge waves excited by an initial mismatch between the detailed initial beam distribution at the bunch ends and the applied focusing waveforms, persisting with multiple damped reflections propagating along the bunch flat-top. Using the induction module we are able to suppress space-charge waves with great accuracy, at amplitudes that include wave steepening prior to the formation of solitary wave trains. The longitudinal dynamics largely dominates when no containment fields are applied, coupling through the natural chromaticity of the ring even within the first turn. After subsequent turns, the bunch elongates and wraps the circumference of the machine multiple times; eventually reaching a point of instability that has also been shown through simulation, obtaining excellent agreement when the detailed longitudinal dynamics of the experiment are carefully incorporated into the model.

  15. A multiscale model for virus capsid dynamics.

    PubMed

    Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei

    2010-01-01

    Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. PMID:20224756

  16. Modeling of non-spherical droplet dynamics

    NASA Astrophysics Data System (ADS)

    Deng, Zheng-Tao; Liaw, Goang-Shin; Chou, Lynn C.

    1993-07-01

    A two-dimensional time-dependent computer code based on the modified Arbitrary Lagrangian Eulerian (ALE) technique, has been developed to simulate non-spherical droplet dynamics and evaporation under convective flows at real rocket combustion chamber conditions. The equations of mass, momentum, energy and species are simultaneously solved for both liquid and gas phases with an accurate dynamic interface tracking. The jump boundary conditions across the deforming droplet surface are obtained by applying the integral forms of conservation of mass, momentum, and energy. At each time step, the interface geometry and flow properties at the droplet surface are implicitly solved by satisfying the interface boundary conditions. A Lagrangian technique was developed to track the arbitrarily moving interface between the liquid droplet and the external gas. An elliptic grid generator is adopted to dynamically reconstruct grids both inside and outside the droplet surface. This code has been used to study droplet oscillation, droplet deformation/breakup, nonspherical droplet evaporation in both low and high pressure convective flows. This presentation briefly describes the numerical algorithm for modeling of the nonspherical droplet dynamics and demonstrates the representative simulation results of nonspherical droplet evaporation at low and high pressure convective flows. Potential applications of this code to rocket combustor design and performance predictions are discussed.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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].

  5. Three-dimensional pharmacophore hypotheses of octopamine/tyramine agonists which inhibit [1-14C]acetate incorporation in Plodia interpunctella.

    PubMed

    Hirashima, Akinori; Eiraku, Tomohiko; Shigeta, Yoko; Kuwano, Eiichi

    2003-01-01

    Three-dimensional pharmacophore hypotheses were built from a set of 36 octopamine (OA)/tyramine (TA) agonists responsible for the inhibition of sex-pheromone production in Plodia interpunctella. Among the ten chemical-featured models generated by a program Catalyst/Hypo, hypotheses including hydrogen-bond acceptor (HBA), hydrogen-bond acceptor aliphatic (HBAl), hydrophobic (Hp), hydrophobic aromatic (HpAr) and hydrophobic aliphatic (HpAl) features were considered to be important and predictive in evaluating OA/TA agonists. Active agonists mapped well onto all the features of the hypothesis such as HBA, HBAl, Hp, HpAr and HpAl features. On the other hand, inactive compounds were shown to be poorly capable of achieving an energetically favorable conformation shared by the active molecules in order to fit the 3-D chemical-feature pharmacophore models. Those hypotheses are considered to be used in designing new leads for hopefully more active compounds. Further research on the comparison of models from the agonists may help elucidate the mechanisms of OA/TA receptor-ligand interactions.

  6. 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

  7. 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.

  8. Integrated computational tools for identification of CCR5 antagonists as potential HIV-1 entry inhibitors: homology modeling, virtual screening, molecular dynamics simulations and 3D QSAR analysis.

    PubMed

    Moonsamy, Suri; Dash, Radha Charan; Soliman, Mahmoud E S

    2014-04-23

    Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated rcv2 value of 0.84 using three principal components and non-cross-validated r2 value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.

  9. Adaptive-network models of collective dynamics

    NASA Astrophysics Data System (ADS)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  10. Toward a dynamic topographic components model.

    PubMed

    Achim, A; Bouchard, S

    1997-09-01

    Möcks' topographic component model (TCM) (Möcks, J. Topographic components model for event-related potentials and some biophysical considerations. IEEE Trans. Biomed. Eng., 1988a, 35: 482-484; Möcks, J. Decomposing event-related potentials: a new topographic components model. Biol. Psychol., 1988b, 26: 199-215) decomposes event-related potentials into components uniquely determined by their respective amplitude profiles across replicates, assuming a constant topography and wave shape for each component. To accommodate possible changes in the component expression across conditions, a dynamic version of TCM is investigated which further admits component modulation in time scale. Twenty test problems were synthesized, incorporating two arbitrary topographies each activated with its own arbitrary wave shape modified, across two conditions, in amplitude, onset and duration. Seventeen problems were perfectly solved, with substantial success on the remaining three, confirming that component jitter or stretching can even help component identification.

  11. 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.

  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. 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.

  14. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

  15. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, R.M.; Kery, M.; Royle, J. Andrew; Plattner, M.

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species-and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity. ?? 2010 by the Ecological Society of America.

  16. Dynamical model for light composite fermions

    NASA Astrophysics Data System (ADS)

    Derman, Emanuel

    1981-04-01

    A simple dynamical model for the internal structure of the three light lepton and quark generations (νe,e,u,d), (νμ,μ,c,s), and (ντ,τ,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L∘,L-,U,D) with the same (SU3)c×SU2×U1 quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e-=[L-H], μ-=[L-HH], τ-=[L-HHH]. It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest MH~16 TeV and MF~100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as μ-->eδ). Phenomenological consequences and tests of the model are discussed.

  17. 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

  18. 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.

  19. 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.

  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. 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.

  4. 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

  5. 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.

  6. 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

  7. Gradient navigation model for pedestrian dynamics

    NASA Astrophysics Data System (ADS)

    Dietrich, Felix; Köster, Gerta

    2014-06-01

    We present a microscopic ordinary differential equation (ODE)-based model for pedestrian dynamics: the gradient navigation model. The model uses a superposition of gradients of distance functions to directly change the direction of the velocity vector. The velocity is then integrated to obtain the location. The approach differs fundamentally from force-based models needing only three equations to derive the ODE system, as opposed to four in, e.g., the social force model. Also, as a result, pedestrians are no longer subject to inertia. Several other advantages ensue: Model-induced oscillations are avoided completely since no actual forces are present. The derivatives in the equations of motion are smooth and therefore allow the use of fast and accurate high-order numerical integrators. At the same time, the existence and uniqueness of the solution to the ODE system follow almost directly from the smoothness properties. In addition, we introduce a method to calibrate parameters by theoretical arguments based on empirically validated assumptions rather than by numerical tests. These parameters, combined with the accurate integration, yield simulation results with no collisions of pedestrians. Several empirically observed system phenomena emerge without the need to recalibrate the parameter set for each scenario: obstacle avoidance, lane formation, stop-and-go waves, and congestion at bottlenecks. The density evolution in the latter is shown to be quantitatively close to controlled experiments. Likewise, we observe a dependence of the crowd velocity on the local density that compares well with benchmark fundamental diagrams.

  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. Simplified dynamic models of grass field ecosystem

    NASA Astrophysics Data System (ADS)

    Zeng, Qingcun; Zeng, Xiaodong; Lu, Peisheng

    1994-12-01

    Some simplified dynamic models of grass field ecosystem are developed and investigated. The maximum simplified one consists of two variables, living grass biomass and soil wetness. The analyses of such models show that there exists only desert regime without grasses if the precipitation p is less than a critical value p c ; the grass biomass continuously depends on p if the interaction between grass biomass and the soil wetness is weak, but the strong interaction results in the bifurcation of grass biomass in the vicinity of p c : the grass biomass is rich as p > p c , but it becomes desertification as p

    model, if the seasonal cycle of model's parameters is introduced. An improved model consists of three variables, i.e. the living grass biomass x, the nonliving grass biomass accumulated on the ground surface y and the soil wetness z. The behaviours of such three variables model are more complicated. The initial values of y and z play a very important role.

  10. 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.

  11. On dynamic modeling for multiscale turbulence problems

    NASA Astrophysics Data System (ADS)

    Chester, Stuart

    Simulating multiscale flows is a challenge because of the vast computational resources required to follow the large number of degrees of freedom involved. The dynamic procedure (Germano et al., 1991) is a powerful modeling tool in the simulation of inherently multiscale turbulent flows, and is the basis for the two main parts of this work. In the first part, high-Reynolds-number flow over tree-like fractals is considered, with emphasis on the drag forces produced. Using large-eddy simulation (LES) of flow over prefractals with multiple branch generations, the dependence of the tree drag on the inner cutoff scale of the fractal is studied. It is found that the convergence of the drag coefficient towards a value that is cutoff-scale independent is slow enough that directly resolving the geometry of all the relevant small-scale branches is highly impractical. To address this fundamental difficulty, a new numerical modeling technique called Renormalized Numerical Simulation (RNS) is introduced. RNS models the drag of the unresolved branches using drag coefficients measured from both resolved branches and unresolved branches (as modeled in previous iterations of the procedure). The RNS technique and its convergence properties are tested by means of a series of simulations using different levels of resolution. Then, RNS is used to investigate the influence of the tree fractal dimension on the tree drag coefficient. Results illustrate that RNS enables numerical modeling of physical processes associated with fractal geometries using affordable computational resolution. The second part of this work is an analysis of the errors incurred by replacing the test-filtering operator by its truncated Taylor-series expansion, in an effort to simplify implementation of the dynamic procedure in simulations of complex-geometry flows. Errors are quantified using a priori and a posteriori tests of forced isotropic turbulence. Results indicate that second-order truncation of the Taylor

  12. Dynamic modelling of packaging material flow systems.

    PubMed

    Tsiliyannis, Christos A

    2005-04-01

    A dynamic model has been developed for reused and recycled packaging material flows. It allows a rigorous description of the flows and stocks during the transition to new targets imposed by legislation, product demand variations or even by variations in consumer discard behaviour. Given the annual reuse and recycle frequency and packaging lifetime, the model determines all packaging flows (e.g., consumption and reuse) and variables through which environmental policy is formulated, such as recycling, waste and reuse rates and it identifies the minimum number of variables to be surveyed for complete packaging flow monitoring. Simulation of the transition to the new flow conditions is given for flows of packaging materials in Greece, based on 1995--1998 field inventory and statistical data. PMID:15864957

  13. 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

  14. 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.

  15. 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

  16. 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).

  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 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.

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Computational modeling of intraocular gas dynamics.

    PubMed

    Noohi, P; Abdekhodaie, M J; Cheng, Y L

    2015-12-18

    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.

  5. A Dynamic Fountain Model for Lunar Dust

    NASA Technical Reports Server (NTRS)

    Stubbs, T. J.; Vondrak, R. R.; Farrell, W. M.

    2005-01-01

    During the Apollo era of exploration it was discovered that sunlight was scattered at the terminators giving rise to horizon glow and streamers above the lunar surface. This was observed from the dark side of the Moon during sunset and sunrise by both surface landers and astronauts in orbit. These observations were quite unexpected, as the Moon was thought to be a pristine environment with a negligible atmosphere or exosphere. Subsequent investigations have shown that the sunlight was most likely scattered by electrostatically charged dust grains originating from the surface. It has since been demonstrated that this dust population could have serious implications for astronomical observations from the lunar surface. The lunar surface is electrostatically charged by the Moon s large-scale interaction with the local plasma environment and the photoemission of electrons due to solar ultra-violet (UV) light and X-rays. The like-charged surface and dust grains then act to repel each other, such that under certain conditions the dust grains are lifted above the surface. We present a dynamic fountain model which can explain how sub-micron dust is able to reach altitudes of up to approximately 100 km above the lunar surface. Previous static dust levitation models are most applicable to the heavier micron-sized grains in close proximity proximity to the surface, but they cannot explain the presence of extremely light grains at high altitudes. If we relax the static constraint applied to previous models, and instead assume that the grains are in constant motion (under the action of dynamic forces), a new picture emerges for the behavior of sub-micron lunar dust.

  6. 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.

  7. 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.

  8. Modelling the Congo basin ecosystems with a dynamic vegetation model

    NASA Astrophysics Data System (ADS)

    Dury, Marie; Hambuckers, Alain; Trolliet, Franck; Huynen, Marie-Claude; Haineaux, Damien; Fontaine, Corentin M.; Fayolle, Adeline; François, Louis

    2014-05-01

    The scarcity of field observations in some parts of the world makes difficult a deep understanding of some ecosystems such as humid tropical forests in Central Africa. Therefore, modelling tools are interesting alternatives to study those regions even if the lack of data often prevents sharp calibration and validation of the model projections. Dynamic vegetation models (DVMs) are process-based models that simulate shifts in potential vegetation and its associated biogeochemical and hydrological cycles in response to climate. Initially run at the global scale, DVMs can be run at any spatial scale provided that climate and soil data are available. In the framework of the BIOSERF project ("Sustainability of tropical forest biodiversity and services under climate and human pressure"), we use and adapt the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) to study the Congo basin vegetation dynamics. The field campaigns have notably allowed the refinement of the vegetation representation from plant functional types (PFTs) to individual species through the collection of parameters such as the specific leaf area or the leaf C:N ratio of common tropical tree species and the location of their present-day occurrences from literature and available database. Here, we test the model ability to reproduce the present spatial and temporal variations of carbon stocks (e.g. biomass, soil carbon) and fluxes (e.g. gross and net primary productivities (GPP and NPP), net ecosystem production (NEP)) as well as the observed distribution of the studied species over the Congo basin. In the lack of abundant and long-term measurements, we compare model results with time series of remote sensing products (e.g. vegetation leaf area index (LAI), GPP and NPP). Several sensitivity tests are presented: we assess consecutively the impacts of the level at which the vegetation is simulated (PFTs or species), the spatial resolution and the initial land

  9. 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.

  10. 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.

  11. Nonlinear dynamical model of human gait.

    PubMed

    West, Bruce J; Scafetta, Nicola

    2003-05-01

    We present a nonlinear dynamical model of the human gait control system in a variety of gait regimes. The stride-interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations becomes more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. Human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way. PMID:12786188

  12. Nonlinear dynamical model of human gait

    NASA Astrophysics Data System (ADS)

    West, Bruce J.; Scafetta, Nicola

    2003-05-01

    We present a nonlinear dynamical model of the human gait control system in a variety of gait regimes. The stride-interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations becomes more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. Human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way.

  13. 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

  14. Dynamical Downscaling Technique for Global Climate Model

    NASA Astrophysics Data System (ADS)

    Yoshimura, K.; Kanamitsu, M.

    2007-12-01

    Aiming at producing higher resolution global reanalysis datasets from coarse 200 km resolution reanalysis, a global version of the dynamical downscaling using a global spectral model (GSM) is developed. A variant of spectral nudging, the scale-selective bias correction (SSBC) developed for regional models is modified in the following manner to adapt it to the global domain; 1) temperature is nudged in addition to the zonal and meridional components of winds, and 2) humidity is excluded from any nudging or correction. The downscaling was performed using T248L28 (about 50 km resolution) global model for 2001, driven by NCEP/NCAR Reanalysis 2 (T62L28 resolution). Evaluation with high-resolution observations showed that the monthly averaged surface temperature and daily variation of precipitation become better than the Reanalysis over the globe. It was found that humidity plays a significant role for a significant positive bias of global precipitation in the downscaled simulation. Over North America, surface wind speed and temperature become better, and over Japan, the diurnal pattern of surface temperature is much improved, as are wind speed and precipitation, but not humidity. This study suggests that the global downscaling is a viable and economical method to obtain high- resolution reanalysis without re-running a very expensive high-resolution full data assimilation.

  15. 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.

  16. 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

  17. Dynamic modeling of orographically induced precipitation

    NASA Technical Reports Server (NTRS)

    Barros, Ana Paula; Lettenmaier, P.

    1994-01-01

    Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

  18. 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…

  19. 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.

  20. Lake eutrophication management modeling using dynamic programming.

    PubMed

    Kuo, Jan-Tai; Hsieh, Pin-Hui; Jou, Wei-Shin

    2008-09-01

    Lake eutrophication problems have received considerable attention in Taiwan, especially because they relate to the quality of drinking water. In this study, steady-state river water quality and lake eutrophication models are solved using dynamic programming algorithms to find the nutrient removal rates for eutrophication control during dry season. The kinetic cycle of chlorophyll-a, phosphorus and nitrogen for a complete-mixed lake is considered in the optimization framework. The Newton-iterative technique is adopted to solve the nonlinear equations for the steady-state lake eutrophication model. The optimization framework is applied to Cheng-Ching Lake in southern Taiwan. Several nutrient loading scenarios for eutrophication control are studied. Optimization results for nutrient removal rates and corresponding wastewater treatment capacities of each reach of the Kao-Ping River define the least cost approach to lake eutrophication control. A natural purification method, structural free water surface wetland, is also suggested to save more investment and improve river water quality at the same time.

  1. 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.

  2. 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.

  3. Design, synthesis, 3D pharmacophore, QSAR, and docking studies of carboxylic acid derivatives as Histone Deacetylase inhibitors and cytotoxic agents.

    PubMed

    Abdel-Atty, Mona M; Farag, Nahla A; Kassab, Shaymaa E; Serya, Rabah A T; Abouzid, Khaled A M

    2014-12-01

    In this study, five series of (E)-6-(4-substituted phenyl)-4-oxohex-5-enoic acids IIb-f (E), (E)-3-(4-(substituted)-phenyl)acrylic acids IIIa-g (E), 4-(4-(substituted)phenylamino)-4-oxobutanoic acids VIa,b,e, 5-(4-(substituted)phenylamino)-5-oxopentanoic acids VIIa,f and 2-[(4-(substituted)phenyl) carbamoyl]benzoic acids VIIIa,e were designed and synthesized. Selected compounds were screened in vitro for their cytotoxic effect on 60 human NCI tumor cell lines. Compound IIf (E) displayed significant inhibitory activity against NCI Non-Small Cell Lung A549/ATCC Cancer cell line (68% inhibition) and NCI-H460 Cancer cell line (66% inhibition). Moreover, the final compounds were evaluated in vitro for their cytotoxic activity on HepG2 Cancer cell line in which histone deacetylase (HDAC) is overexpressed. Compounds IIc (E), IIf (E), IIIb (E), and IIIg (E) exhibited the highest cytotoxic activity against HepG2 human cancer cell lines with IC50 ranging from 2.27 to 10.71μM. In addition, selected compounds were tested on histone deacetylase isoforms (HDAC1-11). Molecular docking simulation was also carried out for HDLP enzyme to investigate their HDAC binding affinity. In addition, generation of 3D-pharmacophore model and quantitative structure activity relationship (QSAR) models were combined to explore the structural requirements controlling the observed cytotoxic properties.

  4. 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…

  5. Viking 1975 orbiter development test model/Lander dynamic test model, dynamic environmental testing

    NASA Technical Reports Server (NTRS)

    Milder, G.

    1975-01-01

    A series of dynamic environmental tests on the Viking 1975 Orbiter/Lander model provided information regarding damping and linearity. The quality of mode isolation was made with orthogonality checks. A pretest criterion established for orthogonality provided good correlation with test results. Part of the post-test analysis was dedicated to a review of instrumentation selection for control and/or response limiting. Limited load values were also examined.

  6. 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.

  7. 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 proc