Science.gov

Sample records for dynamic pharmacophore model

  1. 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.

  2. 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.

  3. Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies.

    PubMed

    Kalva, Sukesh; Azhagiya Singam, E R; Rajapandian, V; Saleena, Lilly M; Subramanian, V

    2014-04-01

    Matrix metalloproteinase-9 (MMP-9) is an attractive target for anticancer therapy. In the present study ligand based pharmacophore modeling was performed to elucidate the structural elements for a diverse class of MMP-9 inhibitors. The pharmacophore model was validated through Güner-Henry (GH) scoring method. The final pharmacophore model consisted of three hydrogen bond acceptors (HBA), and two ring aromatic regions (RA). This model was utilized to screen the natural compound database to seek novel compounds as MMP-9 inhibitors. The identified hits were validated using molecular docking and molecular dynamics simulation studies. Finally, one compound named Hinokiflavone from Juniperus communis had high binding free energy of -26.54kJ/mol compared with the known inhibitors of MMP-9. Cytotoxicity for hinokiflavone was evaluated by MTT assay. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and gelatinolytic inhibition assay. Results revealed that the natural compounds derived based on the developed pharmacophore model would be useful for further design and development of MMP-9 inhibitors.

  4. Molecular dynamics and pharmacophore modelling studies of different subtype (ALK and EGFR (T790M)) inhibitors in NSCLC.

    PubMed

    Singh, P K; Silakari, O

    2017-03-01

    Extensively validated 3D pharmacophore models for ALK (anaplastic lymphoma kinase) and EGFR (T790M) (epithelial growth factor receptor with acquired secondary mutation) were developed. The pharmacophore model for ALK (r(2) = 0.96, q(2) = 0.692) suggested that two hydrogen bond acceptors and three hydrophobic groups arranged in 3-D space are essential for the binding affinity of ALK inhibitors. Similarly, the pharmacophore model for EGFR (T790M) (r(2) = 0.92, q(2) = 0.72) suggested that the presence of a hydrogen bond acceptor, two hydrogen bond donors and a hydrophobic group plays vital role in binding of an inhibitor of EGFR (T790M). These pharmacophore models allowed searches for novel ALK and EGFR (T790M) dual inhibitors from multiconformer 3D databases (Asinex, Chembridge and Maybridge). Finally, the eight best hits were selected for molecular dynamics simulation, to study the stability of their complexes with both proteins and final binding orientations of these molecules. After molecular dynamics simulations, one hit has been predicted to possess good binding affinity for both ALK and EGFR (T790M), which can be further investigated for its experimental in-vitro/in-vivo activities.

  5. Homology modeling, molecular dynamics, e-pharmacophore mapping and docking study of Chikungunya virus nsP2 protease.

    PubMed

    Singh, Kh Dhanachandra; Kirubakaran, Palani; Nagarajan, Shanthi; Sakkiah, Sugunadevi; Muthusamy, Karthikeyan; Velmurgan, Devadasan; Jeyakanthan, Jeyaraman

    2012-01-01

    To date, no suitable vaccine or specific antiviral drug is available to treat Chikungunya viral (CHIKV) fever. Hence, it is essential to identify drug candidates that could potentially impede CHIKV infection. Here, we present the development of a homology model of nsP2 protein based on the crystal structure of the nsP2 protein of Venezuelan equine encephalitis virus (VEEV). The protein modeled was optimized using molecular dynamics simulation; the junction peptides of a nonstructural protein complex were then docked in order to investigate the possible protein-protein interactions between nsP2 and the proteins cleaved by nsP2. The modeling studies conducted shed light on the binding modes, and the critical interactions with the peptides provide insight into the chemical features needed to inhibit the CHIK virus infection. Energy-optimized pharmacophore mapping was performed using the junction peptides. Based on the results, we propose the pharmacophore features that must be present in an inhibitor of nsP2 protease. The resulting pharmacophore model contained an aromatic ring, a hydrophobic and three hydrogen-bond donor sites. Using these pharmacophore features, we screened a large public library of compounds (Asinex, Maybridge, TOSLab, Binding Database) to find a potential ligand that could inhibit the nsP2 protein. The compounds that yielded a fitness score of more than 1.0 were further subjected to Glide HTVS and Glide XP. Here, we report the best four compounds based on their docking scores; these compounds have IDs of 27943, 21362, ASN 01107557 and ASN 01541696. We propose that these compounds could bind to the active site of nsP2 protease and inhibit this enzyme. Furthermore, the backbone structural scaffolds of these four lead compounds could serve as building blocks when designing drug-like molecules for the treatment of Chikungunya viral fever.

  6. 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.

  7. 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

  8. 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

  9. Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling

    NASA Astrophysics Data System (ADS)

    Bharatham, Kavitha; Bharatham, Nagakumar; Kwon, Yong Jung; Lee, Keun Woo

    2008-12-01

    Allosteric inhibition of protein tyrosine phosphatase 1B (PTP1B), has paved a new path to design specific inhibitors for PTP1B, which is an important drug target for the treatment of type II diabetes and obesity. The PTP1B1-282-allosteric inhibitor complex crystal structure lacks α7 (287-298) and moreover there is no available 3D structure of PTP1B1-298 in open form. As the interaction between α7 and α6-α3 helices plays a crucial role in allosteric inhibition, α7 was modeled to the PTP1B1-282 in open form complexed with an allosteric inhibitor (compound-2) and a 5 ns MD simulation was performed to investigate the relative orientation of the α7-α6-α3 helices. The simulation conformational space was statistically sampled by clustering analyses. This approach was helpful to reveal certain clues on PTP1B allosteric inhibition. The simulation was also utilized in the generation of receptor based pharmacophore models to include the conformational flexibility of the protein-inhibitor complex. Three cluster representative structures of the highly populated clusters were selected for pharmacophore model generation. The three pharmacophore models were subsequently utilized for screening databases to retrieve molecules containing the features that complement the allosteric site. The retrieved hits were filtered based on certain drug-like properties and molecular docking simulations were performed in two different conformations of protein. Thus, performing MD simulation with α7 to investigate the changes at the allosteric site, then developing receptor based pharmacophore models and finally docking the retrieved hits into two distinct conformations will be a reliable methodology in identifying PTP1B allosteric inhibitors.

  10. 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.

  11. Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies.

    PubMed

    Hatmal, Ma'mon M; Jaber, Shadi; Taha, Mutasem O

    2016-12-01

    Ligand-based pharmacophore modeling require relatively long lists of active compounds, while a pharmacophore based on a single ligand-receptor crystallographic structure is often promiscuous. These problems prompted us to combine molecular dynamics (MD) simulation with ligand-receptor contacts analysis as means to develop valid pharmacophore model(s). The particular ligand-receptor complex is allowed to perturb over a few nano-seconds using MD simulation. Subsequently, ligand-receptor contact points (≤2.5 Å) are identified. Ligand-receptor contacts maintained above certain threshold during molecular dynamics simulation are considered critical and used to guide pharmacophore development. We termed this method as Molecular-Dynamics Based Ligand-Receptor Contact Analysis. We implemented this new methodology to develop valid pharmacophore models for check point kinase 1 (Chk1) and beta-secretase 1 (BACE1) inhibitors as case studies. The resulting pharmacophore models were validated by receiver operating characteristic curved analysis against inhibitors obtained from CHEMBL database.

  12. Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies

    NASA Astrophysics Data System (ADS)

    Hatmal, Ma'mon M.; Jaber, Shadi; Taha, Mutasem O.

    2016-12-01

    Ligand-based pharmacophore modeling require relatively long lists of active compounds, while a pharmacophore based on a single ligand-receptor crystallographic structure is often promiscuous. These problems prompted us to combine molecular dynamics (MD) simulation with ligand-receptor contacts analysis as means to develop valid pharmacophore model(s). The particular ligand-receptor complex is allowed to perturb over a few nano-seconds using MD simulation. Subsequently, ligand-receptor contact points (≤2.5 Å) are identified. Ligand-receptor contacts maintained above certain threshold during molecular dynamics simulation are considered critical and used to guide pharmacophore development. We termed this method as Molecular-Dynamics Based Ligand-Receptor Contact Analysis. We implemented this new methodology to develop valid pharmacophore models for check point kinase 1 (Chk1) and beta-secretase 1 (BACE1) inhibitors as case studies. The resulting pharmacophore models were validated by receiver operating characteristic curved analysis against inhibitors obtained from CHEMBL database.

  13. Flexible 3D pharmacophores as descriptors of dynamic biological space.

    PubMed

    Nettles, James H; Jenkins, Jeremy L; Williams, Chris; Clark, Alex M; Bender, Andreas; Deng, Zhan; Davies, John W; Glick, Meir

    2007-10-01

    Development of a pharmacophore hypothesis related to small-molecule activity is pivotal to chemical optimization of a series, since it defines features beneficial or detrimental to activity. Although crystal structures may provide detailed 3D interaction information for one molecule with its receptor, docking a different ligand to that model often leads to unreliable results due to protein flexibility. Graham Richards' lab was one of the first groups to utilize "fuzzy" pattern recognition algorithms taken from the field of image processing to solve problems in protein modeling. Thus, descriptor "fuzziness" was partly able to emulate conformational flexibility of the target while simultaneously enhancing the speed of the search. In this work, we extend these developments to a ligand-based method for describing and aligning molecules in flexible chemical space termed FEature POint PharmacophoreS (FEPOPS), which allows exploration of dynamic biological space. We develop a novel, combinatorial algorithm for molecular comparisons and evaluate it using the WOMBAT dataset. The new approach shows superior retrospective virtual screening performance than earlier shape-based or charge-based algorithms. Additionally, we use target prediction to evaluate how FEPOPS alignments match the molecules biological activity by identifying the atoms and features that make the key contributions to overall chemical similarity. Overall, we find that FEPOPS are sufficiently fuzzy and flexible to find not only new ligand scaffolds, but also challenging molecules that occupy different conformational states of dynamic biological space as from induced fits.

  14. Integrating Pharmacophore into Membrane Molecular Dynamics Simulations to Improve Homology Modeling of G Protein-coupled Receptors with Ligand Selectivity: A2A Adenosine Receptor as an Example.

    PubMed

    Zeng, Lingxiao; Guan, Mengxin; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren

    2015-12-01

    Homology modeling has been applied to fill in the gap in experimental G protein-coupled receptors structure determination. However, achievement of G protein-coupled receptors homology models with ligand selectivity remains challenging due to structural diversity of G protein-coupled receptors. In this work, we propose a novel strategy by integrating pharmacophore and membrane molecular dynamics (MD) simulations to improve homology modeling of G protein-coupled receptors with ligand selectivity. To validate this integrated strategy, the A2A adenosine receptor (A2A AR), whose structures in both active and inactive states have been established, has been chosen as an example. We performed blind predictions of the active-state A2A AR structure based on the inactive-state structure and compared the performance of different refinement strategies. The blind prediction model combined with the integrated strategy identified ligand-receptor interactions and conformational changes of key structural elements related to the activation of A2 A AR, including (i) the movements of intracellular ends of TM3 and TM5/TM6; (ii) the opening of ionic lock; (iii) the movements of binding site residues. The integrated strategy of pharmacophore with molecular dynamics simulations can aid in the optimization in the identification of side chain conformations in receptor models. This strategy can be further investigated in homology modeling and expand its applicability to other G protein-coupled receptor modeling, which should aid in the discovery of more effective and selective G protein-coupled receptor ligands. © 2015 John Wiley & Sons A/S.

  15. 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.

  16. A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis, molecular docking, density functional and molecular dynamics simulation study.

    PubMed

    Choubey, Sanjay K; Jeyaraman, Jeyakanthan

    2016-11-01

    Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r(2)=0.82 and cross validation correlation co-efficient q(2)=0.70. External validation result displays high predictive power with r(2) (o) value of 0.88 and r(2) (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (-11.17kcal/mol) and lower docking energy -37.84kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein.

  17. Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery.

    PubMed

    Moorthy, N S Hari Narayana; Sousa, Sergio F; Ramos, Maria J; Fernandes, Pedro A

    2016-12-01

    Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10 ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein-ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π-π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3-4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1-3 Å for Acc & ML and 1-2 Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1-2 Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.

  18. Molecular modeling of the 3D structure of 5-HT(1A)R: discovery of novel 5-HT(1A)R agonists via dynamic pharmacophore-based virtual screening.

    PubMed

    Xu, Lili; Zhou, Shanglin; Yu, Kunqian; Gao, Bo; Jiang, Hualiang; Zhen, Xuechu; Fu, Wei

    2013-12-23

    The serotonin receptor subtype 1A (5-HT(1A)R) has been implicated in several neurological conditions, and potent 5-HT(1A)R agonists have therapeutic potential for the treatment of depression, anxiety, schizophrenia, and Parkinson's disease. In the present study, a homology model of 5-HT(1A)R was built based on the latest released high-resolution crystal structure of the β₂AR in its active state (PDB: 3SN6). A dynamic pharmacophore model, which takes the receptor flexibility into account, was constructed, validated, and applied to our dynamic pharmacophore-based virtual screening approach with the aim to identify potential 5-5-HT(1A)R agonists. The obtained hits were subjected to 55-HT(1A)R binding and functional assays, and 10 compounds with medium or high K(i) and EC₅₀ values were identified. Among them, FW01 (K(i) = 51.9 nM, EC₅₀ = 7 nM) was evaluated as the strongest agonist for 5-HT(1A)R. The active 5-HT(1A)R model and dynamic pharmacophore model obtained from this study can be used for future discovery and design of novel 5-HT(1A)R agonists. Also, by integrating all computational and available experimental data, a stepwise 5-HT(1A)R signal transduction model induced by agonist FW01 was proposed.

  19. Novel PARP-1 Inhibitor Scaffolds Disclosed by a Dynamic Structure-Based Pharmacophore Approach

    PubMed Central

    Baptista, Salete J.; Silva, Maria M. C.; Moroni, Elisabetta; Meli, Massimiliano; Colombo, Giorgio; Dinis, Teresa C. P.; Salvador, Jorge A. R.

    2017-01-01

    PARP-1 inhibition has been studied over the last decades for the treatment of various diseases. Despite the fact that several molecules act as PARP-1 inhibitors, a reduced number of compounds are used in clinical practice. To identify new compounds with a discriminatory PARP-1 inhibitory function, explicit-solvent molecular dynamics simulations using different inhibitors bound to the PARP-1 catalytic domain were performed. The representative structures obtained were used to generate structure-based pharmacophores, taking into account the dynamic features of receptor-ligand interactions. Thereafter, a virtual screening of compound databases using the pharmacophore models obtained was performed and the hits retrieved were subjected to molecular docking-based scoring. The drug-like molecules featuring the best ranking were evaluated for their PARP-1 inhibitory activity and IC50 values were calculated for the top scoring docked compounds. Altogether, three new PARP-1 inhibitor chemotypes were identified. PMID:28122037

  20. Four-component pharmacophore model for endomorphins toward μ opioid receptor subtypes.

    PubMed

    Wu, Yng-Ching; Jaglinski, Tim; Hsieh, Jin-Yuan; Chiu, Jia-Jyun; Chiang, Tzen-Yuh; Hwang, Chi-Chuan

    2012-02-01

    In the present work, a series of simulation tools were used to determine structure-activity relationships for the endomorphins (EMs) and derive μ-pharmacophore models for these peptides. Potential lowest energy conformations were determined in vacuo by systematically varying the torsional angles of the Tyr(1)-Pro(2) (ω(1)) and Pro(2)-Trp(3)/Phe(3) (ω(2)) as tuning parameters in AM1 calculations. These initial models were then exposed to aqueous conditions via molecular dynamics simulations. In aqueous solution, the simulations suggest that endomorphin conformers strongly favor the trans/trans pair of the ω(1)/ω(2) amide bonds. From two-dimensional probability distributions of the ring-to-ring distances with respect to the pharmacophoric angles for EMs, a selectivity range of μ(1) is ca. 8.3 ~ 10.5 Å for endomorphin-2 and selectivity range of μ(2) is ca. 10.5 ~ 13.0 Å for endomorphin-1 were determined. Four-component μ-pharmacophore models are proposed for EMs and are compared to the previously published δ- and κ-pharmacophore models.

  1. Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

    PubMed

    Islam, Md Ataul; Pillay, Tahir S

    2017-01-21

    In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB.

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

    PubMed

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

    2015-12-28

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

  3. 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

  4. Exploring the potential of protein-based pharmacophore models in ligand pose prediction and ranking

    PubMed Central

    Hu, Bingjie; Lill, Markus A.

    2013-01-01

    Protein-based pharmacophore models derived from the protein binding site atoms without the inclusion of any ligand information have become more popular in virtual screening studies. However, the accuracy of protein-based pharmacophore models for reproducing the critical protein-ligand interactions has never been explicitly assessed. In this study, we used known protein-ligand contacts from a large set of experimentally determined protein-ligand complexes to assess the quality of the protein-based pharmacophores in reproducing these critical contacts. We demonstrate how these contacts can be used to optimize the pharmacophore generation procedure to produce pharmacophore models that optimally cover the known protein-ligand interactions. Finally, we explored the potential of the optimized protein-based pharmacophore models for pose prediction and pose rankings. Our results demonstrate that there are significant variations in the success of protein-based pharmacophore models to reproduce native contacts and consequently native ligand poses dependent on the details of the pharmacophore-generation process. We show that the generation of optimized protein-based pharmacophore models is a promising approach for ligand pose prediction and pose rankings. PMID:23621564

  5. Pharmacophore modeling and parallel screening for PPAR ligands

    NASA Astrophysics Data System (ADS)

    Markt, Patrick; Schuster, Daniela; Kirchmair, Johannes; Laggner, Christian; Langer, Thierry

    2007-10-01

    We describe the generation and validation of pharmacophore models for PPARs, as well as a large scale validation of the parallel screening approach by screening PPAR ligands against a large database of structure-based models. A large test set of 357 PPAR ligands was screened against 48 PPAR models to determine the best models for agonists of PPAR-α, PPAR-δ, and PPAR-γ. Afterwards, a parallel screen was performed using the 357 PPAR ligands and 47 structure-based models for PPARs, which were integrated into a 1537 models comprising in-house pharmacophore database, to assess the enrichment of PPAR ligands within the PPAR hypotheses. For these purposes, we categorized the 1537 database models into 181 protein targets and developed a score that ranks the retrieved targets for each ligand. Thus, we tried to find out if the concept of parallel screening is able to predict the correct pharmacological target for a set of compounds. The PPAR target was ranked first more often than any other target. This confirms the ability of parallel screening to forecast the pharmacological active target for a set of compounds.

  6. Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Database screening using receptor-based pharmacophores is a computer-aided drug design technique that uses the structure of the target molecule (i.e. protein) to identify novel ligands that may bind to the target. Typically receptor-based pharmacophore modeling methods only consider a single or limited number of receptor conformations and map out the favorable binding patterns in vacuum or with a limited representation of the aqueous solvent environment, such that they may suffer from neglect of protein flexibility and desolvation effects. Site-Identification by Ligand Competitive Saturation (SILCS) is an approach that takes into account these, as well as other, properties to determine 3-dimensional maps of the functional group-binding patterns on a target receptor (i.e. FragMaps). In this study, a method to use the FragMaps to automatically generate receptor-based pharmacophore models is presented. It converts the FragMaps into SILCS pharmacophore features including aromatic, aliphatic, hydrogen-bond donor and acceptor chemical functionalities. The method generates multiple pharmacophore hypotheses that are then quantitatively ranked using SILCS grid free energies. The pharmacophore model generation protocol is validated using three different protein targets, including using the resulting models in virtual screening. Improved performance and efficiency of the SILCS derived pharmacophore models as compared to published docking studies, as well as a recently developed receptor-based pharmacophore modeling method is shown, indicating the potential utility of the approach in rational drug design.

  7. Site-Identification by Ligand Competitive Saturation (SILCS) Assisted Pharmacophore Modeling

    PubMed Central

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

    2014-01-01

    Database screening using receptor-based pharmacophores is a computer-aided drug design technique that uses the structure of the target molecule (i.e. protein) to identify novel ligands that may bind to the target. Typically receptor-based pharmacophore modeling methods only consider a single or limited number of receptor conformations and map out the favorable binding patterns in vacuum or with a limited representation of the aqueous solvent environment, such that they may suffer from neglect of protein flexibility and desolvation effects. Site-Identification by Ligand Competitive Saturation (SILCS) is an approach that takes into account these, as well as other, properties to determine 3-dimensional maps of the functional group-binding patterns on a target receptor (i.e. FragMaps). In this study, a method to use the FragMaps to automatically generate receptor-based pharmacophore models is presented. It converts the FragMaps into SILCS pharmacophore features including aromatic, aliphatic, hydrogen-bond donor and acceptor chemical functionalities. The method generates multiple pharmacophore hypotheses that are then quantitatively ranked using SILCS grid free energies. The pharmacophore model generation protocol is validated using three different protein targets, including using the resulting models in virtual screening. Improved performance and efficiency of the SILCS derived pharmacophore models as compared to published docking studies, as well as a recently developed receptor-based pharmacophore modeling method is shown, indicating the potential utility of the approach in rational drug design. PMID:24610239

  8. Integrated ligand based pharmacophore model derived from diverse FAAH covalent ligand classes.

    PubMed

    Shen, Lingling; Huang, Hongwei; Makriyannis, Alexandros; Fisher, Luke S

    2012-12-01

    3D pharmacophore modeling is an important computational methodology for ligand-enzyme binding interactions in drug discovery. More specifically, a consensus pharmacophore model derived from diverse ligands is a key determinant upon which the prediction power of computational models is based for designing novel ligands. In this work, by merging the important pharmacophore features based on four classes of covalent FAAH ligands, and then integrating the exclusion volume spheres derived from the crystal structure, we created for the first time an integrated FAAH pharmacophore model to describe the ligand-enzyme binding interactions. This new integrated FAAH pharmacophore model can correctly predict the covalent ligand binding mode, which correlates with the SAR data. The study is expected to provide insights into novel covalent ligand-FAAH binding interactions, and facilitate the design of covalent ligands against FAAH.

  9. High-throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening.

    PubMed

    Steindl, Theodora M; Schuster, Daniela; Wolber, Gerhard; Laggner, Christian; Langer, Thierry

    2006-12-01

    In order to assess bioactivity profiles for small organic molecules we propose to use parallel pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding pharmaco-phores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of pharmacophore queries.

  10. High-throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening

    NASA Astrophysics Data System (ADS)

    Steindl, Theodora M.; Schuster, Daniela; Wolber, Gerhard; Laggner, Christian; Langer, Thierry

    2006-12-01

    In order to assess bioactivity profiles for small organic molecules we propose to use parallel pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding pharmacophores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of pharmacophore queries.

  11. 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

  12. Comparative and pharmacophore model for deacetylase SIRT1

    NASA Astrophysics Data System (ADS)

    Huhtiniemi, Tero; Wittekindt, Carsten; Laitinen, Tuomo; Leppänen, Jukka; Salminen, Antero; Poso, Antti; Lahtela-Kakkonen, Maija

    2006-09-01

    Sirtuins are NAD-dependent histone deacetylases, which cleave the acetyl-group from acetylated proteins, such as histones but also the acetyl groups from several transcription factors, and in this way can change their activities. Of all seven mammalian SirTs, the human sirtuin SirT1 has been the most extensively studied. However, there is no crystal structure or comparative model reported for SirT1. We have therefore built up a three-dimensional comparison model of the SirT1 protein catalytic core (domain area from residues 244 to 498 of the full length SirT1) in order to assist in the investigation of active site-ligand interactions and in the design of novel SirT1 inhibitors. In this study we also propose the binding-mode of recently reported set of indole-based inhibitors in SirT1. The site of interaction and the ligand conformation were predicted by the use of molecular docking techniques. To distinguish between active and inactive compounds, a post-docking filter based on H-bond network was constructed. Docking results were used to investigate the pharmacophore and to identify a filter for database mining.

  13. Generation, validation, and utilization of a three-dimensional pharmacophore model for EP3 antagonists.

    PubMed

    Mishra, Rama K; Singh, Jasbir

    2010-08-23

    Studies reported here are aimed to investigate the important structural features that characterize the human EP(3) antagonists. Based on the knowledge of low-energy conformation of the endogenous ligand, the initial hit analogs were prepared. Subsequently, a ligand-based lead optimization approach using pharmacophore model generation was utilized. A 5-point pharmacophore using a training set of 19 compounds spanning the IC(50) data over 4-log order was constructed using the HypoGen module of Catalyst. Following pharmacophore customization, using a linear structure-activity regression equation, a six feature three-dimensional predictive pharmacophore model, P6, was built, which resulted in improved predictive power. The P6 model was validated using a test set of 11 compounds providing a correlation coefficient (R(2)) of 0.90 for predictive versus experimental EP(3) IC(50) values. This pharmacophore model has been expanded to include diverse chemotypes, and the predictive ability of the customized pharmacophore has been tested.

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

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2016-04-07

    Pharmacophore modeling, molecular docking, and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 2-phenylpyrimidine series as PDE4B selective inhibitors. A five point pharmacophore model was developed using 87 molecules having pIC50 ranging from 8.52 to 5.07. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R(2)=0.918), cross validation coefficient (Q(2)=0.852), and F value (175) at 4 component PLS factor. The external validation indicated that our QSAR model possessed high predictive power (R(2)=0.70). The generated model was further validated by enrichment studies using the decoy test. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviation. A 10ns molecular dynamics simulation confirmed the docking results of both stability of the 1XMU-ligand complex and the presumed active conformation. Further, similar orientation was observed between the superposition of the conformations of 85 after MD simulation and best XP-docking pose; MD simulation and 3D-QSAR pose; best XP-docking and 3D-QSAR poses. Outcomes of the present study provide insight in designing novel molecules with better PDE4B selective inhibitory activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. 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

    2016-07-08

    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.

  16. Protein pharmacophore selection using hydration-site analysis

    PubMed Central

    Hu, Bingjie; Lill, Markus A.

    2012-01-01

    Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751

  17. Identification of new novel scaffold for Aurora A inhibition by pharmacophore modeling and virtual screening.

    PubMed

    Chavan, Sayalee R; Dash, Radha Charan; Alam, M Sarwar; Hirwani, Raj R

    2014-11-01

    Aurora kinases belong to family of highly conserved serine/threonine protein kinases that are involved in diverse cell cycle events and play a major role in regulation of cell division. Abnormal expression of Aurora kinases may lead to cancer; hence, these are considered as a potential target in cancer treatment. In this research article, we identified three novel Aurora A inhibitors using modern computational tools. A four-point common 3D pharmacophore hypothesis of Aurora A (AurA) inhibitors was developed using a diverse set of 55 thienopyrimidine derivatives. A three-dimensional quantitative structure-activity relationship (3D-QSAR) study was carried out using atom-based alignment of diverse set of 55 molecules to evaluate the structure- activity relationships. Docking and 3D-QSAR studies were performed with the 3D structure of AurA to evaluate the generated pharmacophore. The pharmacophore model and 3D-QSAR results complemented the results of our docking study. The pharmacophore hypothesis, which yields the best results, was used to screen the Zinc 'clean drug-like' database. Various database filters such as 3D-arrangement of pharmacophoric features, predicted activity and binding interaction score were used to retrieve hits having potential AurA inhibition activity.

  18. Combinatorial pharmacophore modeling of organic cation transporter 2 (OCT2) inhibitors: insights into multiple inhibitory mechanisms.

    PubMed

    Xu, Yuan; Liu, Xian; Li, Shanshan; Zhou, Nannan; Gong, Likun; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Jiang, Hualiang; Chen, Kaixian

    2013-12-02

    Organic cation transporter 2 (OCT2) is responsible for the entry step of many drugs in renal elimination, of which the changing activity may cause unwanted drug-drug interactions (DDIs). To develop drugs with favorable safety profile and provide instruction for rational clinical drug administration, it is of great interest to investigate the multiple mechanisms of OCT2 inhibition. In this study, we designed a combinatorial scheme to screen the optimum combination of pharmacophores from a pool of hypotheses established based on 162 OCT2 inhibitors. Among them, one single pharmacophore hypothesis represents a potential binding mode that may account for one unique inhibitory mechanism, and the obtained pharmacophore combination describes the multimechanisms of OCT2 inhibition. The final model consists of four individual pharmacophores, i.e., DHPR18, APR2, PRR5 and HHR4. Given a query ligand, it is considered as an inhibitor if it matches at least one of the hypotheses, or a noninhibitor if it fails to match any of four hypotheses. Our combinatorial pharmacophore model performs reasonably well to discriminate inhibitors and noninhibitors, yielding an overall accuracy around 0.70 for a test set containing 81 OCT2 inhibitors and 218 noninhibitors. Intriguingly, we found that the number of matched hypotheses was positively correlated with inhibition rate, which coincides with the pharmacophore modeling result of P-gp substrate binding. Further analysis suggested that the hypothesis PRR5 was responsible for competitive inhibition of OCT2, and other hypotheses were important for interaction between the inhibitor and OCT2. In light of the results, a hypothetical model for inhibiting transporting mediated by OCT2 was proposed.

  19. Dual Binding Site and Selective Acetylcholinesterase Inhibitors Derived from Integrated Pharmacophore Models and Sequential Virtual Screening

    PubMed Central

    Gupta, Shikhar; Mohan, C. Gopi

    2014-01-01

    In this study, we have employed in silico methodology combining double pharmacophore based screening, molecular docking, and ADME/T filtering to identify dual binding site acetylcholinesterase inhibitors that can preferentially inhibit acetylcholinesterase and simultaneously inhibit the butyrylcholinesterase also but in the lesser extent than acetylcholinesterase. 3D-pharmacophore models of AChE and BuChE enzyme inhibitors have been developed from xanthostigmine derivatives through HypoGen and validated using test set, Fischer's randomization technique. The best acetylcholinesterase and butyrylcholinesterase inhibitors pharmacophore hypotheses Hypo1_A and Hypo1_B, with high correlation coefficient of 0.96 and 0.94, respectively, were used as 3D query for screening the Zinc database. The screened hits were then subjected to the ADME/T and molecular docking study to prioritise the compounds. Finally, 18 compounds were identified as potential leads against AChE enzyme, showing good predicted activities and promising ADME/T properties. PMID:25050335

  20. Pharmacophore modeling using site-identification by ligand competitive saturation (SILCS) with multiple probe molecules.

    PubMed

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

    2015-02-23

    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 molecular dynamics 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, reranking 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.

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

    PubMed

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

    2015-01-01

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

  2. Morphinans and isoquinolines: acetylcholinesterase inhibition, pharmacophore modeling, and interaction with opioid receptors.

    PubMed

    Schuster, Daniela; Spetea, Mariana; Music, Melisa; Rief, Silvia; Fink, Monika; Kirchmair, Johannes; Schütz, Johannes; Wolber, Gerhard; Langer, Thierry; Stuppner, Hermann; Schmidhammer, Helmut; Rollinger, Judith M

    2010-07-15

    Following indications from pharmacophore-based virtual screening of natural product databases, morphinan and isoquinoline compounds were tested in vitro for acetylcholinesterase (AChE) inhibition. After the first screen, active and inactive compounds were used to build a ligand-based pharmacophore model in order to prioritize compounds for biological testing. Among the virtual hits tested, the enrichment of actives was significantly higher than in a random selection of test compounds. The most active compounds were biochemically tested for their activity on mu, delta, and kappa opioid receptors.

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

    PubMed

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

    2016-01-01

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

  4. 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

  5. A specific pharmacophore model of sodium-dependent glucose co-transporter 2 (SGLT2) inhibitors.

    PubMed

    Tang, Chunlei; Zhu, Xiaoyun; Huang, Dandan; Zan, Xin; Yang, Baowei; Li, Ying; Du, Xiaoyong; Qian, Hai; Huang, Wenlong

    2012-06-01

    Sodium-dependent glucose co-transporter 2 (SGLT2) plays a pivotal role in maintaining glucose equilibrium in the human body, emerging as one of the most promising targets for the treatment of diabetes mellitus type 2. Pharmacophore models of SGLT2 inhibitors have been generated with a training set of 25 SGLT2 inhibitors using Discovery Studio V2.1. The best hypothesis (Hypo1(SGLT2)) contains one hydrogen bond donor, five excluded volumes, one ring aromatic and three hydrophobic features, and has a correlation coefficient of 0.955, cost difference of 68.76, RMSD of 0.85. This model was validated by test set, Fischer randomization test and decoy set methods. The specificity of Hypo1(SGLT2) was evaluated. The pharmacophore features of Hypo1(SGLT2) were different from the best pharmacophore model (Hypo1(SGLT1)) of SGLT1 inhibitors we developed. Moreover, Hypo1(SGLT2) could effectively distinguish selective inhibitors of SGLT2 from those of SGLT1. These results indicate that a highly predictive and specific pharmacophore model of SGLT2 inhibitors has been successfully obtained. Then Hypo1(SGLT2) was used as a 3D query to screen databases including NCI and Maybridge for identifying new inhibitors of SGLT2. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five. And several compounds selected from the top ranked hits have been suggested for further experimental assay studies.

  6. Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets

    NASA Astrophysics Data System (ADS)

    Shahin, Rand; Swellmeen, Lubna; Shaheen, Omar; Aboalhaija, Nour; Habash, Maha

    2016-01-01

    Targeting Proviral integration-site of murine Moloney leukemia virus 1 kinase, hereafter called Pim-1 kinase, is a promising strategy for treating different kinds of human cancer. Headed for this a total list of 328 formerly reported Pim-1 kinase inhibitors has been explored and divided based on the pharmacophoric features of the most active molecules into 10 subsets projected to represent potential active binding manners accessible to ligands within the binding pocket of Pim-1 kinase. Discovery Studio 4.1 (DS 4.1) was employed to detect potential pharmacophoric active binding manners anticipated by Pim-1 Kinase inhibitors. The pharmacophoric models were then allowed to compete within Quantitative Structure Activity Relationship (QSAR) framework with other 2D descriptors. Accordingly Genetic algorithm and multiple linear regression investigation were engaged to find the finest QSAR equation that has the best predictive power r 262 2 = 0.70, F = 119.14, r LOO 2 = 0.693, r PRESS 2 against 66 external test inhibitors = 0.71 q2 = 0.55. Three different pharmacophores appeared in the successful QSAR equation this represents three different binding modes for inhibitors within the Pim-1 kinase binding pocket. Pharmacophoric models were later used to screen compounds within the National Cancer Institute database. Several low micromolar Pim-1 Kinase inhibitors were captured. The most potent hits show IC50 values of 0.77 and 1.03 µM. Also, upon analyzing the successful QSAR Equation we found that some polycyclic aromatic electron-rich structures namely 6-Chloro-2-methoxy-acridine can be considered as putative hits for Pim-1 kinase inhibition.

  7. In silico pharmacophore model for tabun-inhibited acetylcholinesterase reactivators: a study of their stereoelectronic properties.

    PubMed

    Bhattacharjee, Apurba K; Kuca, Kamil; Musilek, Kamil; Gordon, Richard K

    2010-01-01

    Organophosphorus (OP) nerve agents that inhibit acetylcholinesterase (AChE; EC 3.1.1.7) function in the nervous system, causing acute intoxication. If untreated, death can result. Inhibited AChE can be reactivated by oximes, antidotes for OP exposure. However, OP intoxication caused by the nerve agent tabun (GA) is particularly resistant to oximes, which poorly reactivate GA-inhibited AChE. In an attempt to develop a rational strategy for the discovery and design of novel reactivators with lower toxicity and increased efficacy in reactivating GA-inhibited AChE, we developed the first in silico pharmacophore model for binding affinity of GA-inhibited AChE from a set of 11 oximes. Oximes were analyzed for stereoelectronic profiles and three-dimensional quantitative structure-activity relationship pharmacophores using ab initio quantum chemical and pharmacophore generation methods. Quantum chemical methods were sequentially used from semiempirical AM1 to hierarchical ab initio calculations to determine the stereoelectronic properties of nine oximes exhibiting affinity for binding to GA-inhibited AChE in vivo. The calculated stereoelectronic properties led us to develop the in silico pharmacophore model using CATALYST methodology. Specific stereoelectronic profiles including the distance between bisquarternary nitrogen atoms of the pyridinium ring in the oximes, hydrophilicity, surface area, nucleophilicity of the oxime oxygen, and location of the molecular orbitals on the isosurfaces have important roles for potencies for reactivating GA-inhibited AChE. The in silico pharmacophore model of oxime affinity for binding to GA-inhibited AChE was found to require a hydrogen bond acceptor, a hydrogen bond donor at the two terminal regions, and an aromatic ring in the central region of the oximes. The model was found to be well-correlated (R = 0.9) with experimental oxime affinity for binding to GA-inhibited AChE. Additional stereoelectronic features relating activity with

  8. Discovery of Novel CXCR2 Inhibitors Using Ligand-Based Pharmacophore Models.

    PubMed

    Ha, Helen; Debnath, Bikash; Odde, Srinivas; Bensman, Tim; Ho, Henry; Beringer, Paul M; Neamati, Nouri

    2015-08-24

    The chemokine receptor CXCR2 is expressed on various immune cells and is essential for neutrophil recruitment and angiogenesis at sites of acute and chronic inflammation caused by tissue injury or infection. CXCR2 and its ligand, CXCL8, are implicated in a number of inflammation-mediated diseases such as chronic obstructive pulmonary disease, cystic fibrosis, and cancer. Though the development of CXCR2-specific small-molecule inhibitors as anti-inflammatory agents has been pursued by pharmaceutical companies within the past decade, there are currently no clinically approved CXCR2 inhibitors. A pharmacophore model based on previously reported CXCR2 antagonists was developed to screen a database of commercially available compounds. Small-molecule compounds identified from the pharmacophore screening were selected for in vitro screening in a cell-based CXCR2-mediated β-arrestin-2 recruitment assay and further characterized in several cell-based assays and lipopolysaccharide (LPS)-induced lung inflammation studies in mice. CX compounds identified from pharmacophore modeling inhibited cell migration, lung and colon cancer cell proliferation, and colony formation. Mechanistic studies of CX4152 showed that this compound inhibits CXCR2 signaling through downregulation of surface CXCR2. Additionally, CX4152 significantly inhibits CXCL8-mediated neutrophil migration and LPS-induced lung inflammation in mice. Using a CXCR2-inhibitor-based pharmacophore model, we identified a novel set of sulfonamides from a diverse library of small molecules. These compounds inhibit CXCR2/β-arrestin-2 association, cell migration and proliferation, and acute inflammation in mouse models. CX compounds identified from our pharmacophore models are potential leads for further optimization and development as anti-inflammatory and anticancer agents.

  9. Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

    PubMed

    Al-Masri, Ihab M; Mohammad, Mohammad K; Taha, Mutasem O

    2008-11-01

    Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

  10. Generation of a homology model of the human histamine H3 receptor for ligand docking and pharmacophore-based screening

    NASA Astrophysics Data System (ADS)

    Schlegel, Birgit; Laggner, Christian; Meier, Rene; Langer, Thierry; Schnell, David; Seifert, Roland; Stark, Holger; Höltje, Hans-Dieter; Sippl, Wolfgang

    2007-08-01

    The human histamine H3 receptor (hH3R) is a G-protein coupled receptor (GPCR), which modulates the release of various neurotransmitters in the central and peripheral nervous system and therefore is a potential target in the therapy of numerous diseases. Although ligands addressing this receptor are already known, the discovery of alternative lead structures represents an important goal in drug design. The goal of this work was to study the hH3R and its antagonists by means of molecular modelling tools. For this purpose, a strategy was pursued in which a homology model of the hH3R based on the crystal structure of bovine rhodopsin was generated and refined by molecular dynamics simulations in a dipalmitoylphosphatidylcholine (DPPC)/water membrane mimic before the resulting binding pocket was used for high-throughput docking using the program GOLD. Alternatively, a pharmacophore-based procedure was carried out where the alleged bioactive conformations of three different potent hH3R antagonists were used as templates for the generation of pharmacophore models. A pharmacophore-based screening was then carried out using the program Catalyst. Based upon a database of 418 validated hH3R antagonists both strategies could be validated in respect of their performance. Seven hits obtained during this screening procedure were commercially purchased, and experimentally tested in a [3H]Nα-methylhistamine binding assay. The compounds tested showed affinities at hH3R with K i values ranging from 0.079 to 6.3 μM.

  11. Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors

    PubMed Central

    2011-01-01

    Background Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study. Methods Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features. Results The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors. Conclusion A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were

  12. BCR-ABL tyrosine kinase inhibitor pharmacophore model derived from a series of phenylaminopyrimidine-based (PAP) derivatives.

    PubMed

    Cui, Jing; Fu, Rao; Zhou, Li-Hua; Chen, Sheng-Ping; Li, Guang-Wu; Qian, Shen-Xian; Liu, Shu

    2013-04-15

    To reveal novel insights into the inhibition of BCR-ABL tyrosine kinase, pharmacophore mapping studies were performed for a series of phenylaminopyrimidine-based (PAP) derivatives, including imatinib (Gleevec). A seven-point pharmacophore model with one hydrophobic group (H), two hydrogen bond donors (D) and four aromatic rings (R) was developed using phase (pharmacophore alignment & scoring engine). The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of 0.886 and a survival score of 4.97 for training set molecules. The model showed excellent predictive power, with a correlation coefficient of Q(2)=0.768 for an external test set of ten molecules. The results obtained from our studies provide a valuable tool for designing new lead molecules with potent activity.

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

    PubMed

    Sindhu, Thangaraj; Srinivasan, Pappu

    2017-04-01

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

  14. 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

  15. 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.

  16. 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

  17. Design, synthesis and pharmacophoric model building of novel substituted nicotinic acid hydrazones with potential antiproliferative activity.

    PubMed

    Abdel-Aziz, Hatem A; Aboul-Fadl, Tarek; Al-Obaid, Abdul-Rahman M; Ghazzali, Mohamed; Al-Dhfyan, Abdullah; Contini, Alessandro

    2012-09-01

    Novel 6-aryl-2-methylnicotinic acid hydrazides 4a-c and their corresponding hydrazones 5a-c and 6a-i were synthesized. X-ray single crystal diffraction of 6h confirmed the chemical structure of hydrazones 6a-i. Antiproliferative activity of the synthetic compounds was investigated against K562 leukemia cell lines. Variable cell growth inhibitory activities were obtained with IC₅₀ range from 24.99 to 66.78 μM where the compound 6c exhibited the maximum activity. Structure activity relationship analysis has been performed and a common pharmacophore model for the synthesized derivatives has been obtained by using the pharmacophore elucidation module of the software MOE. The best model obtained is characterized by two projected locations of potential H-bond donors (F 3 and F4) and two Aromatic annotations (F1 and F2).

  18. 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.

  19. Mycobacterial DNA gyrB inhibitors: Ligand based pharmacophore modelling and in vitro enzyme inhibition studies.

    PubMed

    Saxena, Shalini; Renuka, Janupally; Jeankumar, Variam Ullas; Yogeeswari, Perumal; Sriram, Dharmarajan

    2014-01-01

    Among the topoisomerases, DNA gyrase belongs to the type II classes that catalysing DNA supercoiling or relaxation, catenation or decatenation, knotting or unknotting. It is one of the validated targets for anti-tubercular drug discovery and inhibitors from this group are also active against non-replicating, persistent mycobacteria, which might be important for shortening the duration of TB therapy. From past few years, extensive research was carried out towards potent DNA gyrase inhibitor design. The current review focuses on the most of potent series of DNA gyrase inhibitors and its structure activity relationships (SAR). The current manuscript also reports the current research on identification of potent DNA gyrase inhibitors using ligand based virtual screening approaches. The pharmacophore model was developed and validated against 65 known Mycobacterium smegmatics (MS) DNA Gyrase inhibitors. Validated pharmacophore model consists of HBA, HY, and RA features were essential for DNA Gyrase inhibition and this model was used to screen virtual screening to retrieve potential inhibitors from our in house database. Finally, 15 hits were ranked as potential leads based on pharmacophoric fit value and estimated activity. Furthermore, in-vitro enzymatic inhibition studies were performed for these 15 most promising candidates and these compounds were found to exhibit inhibition at 30 µM.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    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 (<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.

  2. 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

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

    PubMed Central

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

    2016-01-01

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

  4. Design checkpoint kinase 2 inhibitors by pharmacophore modeling and virtual screening techniques.

    PubMed

    Wang, Yen-Ling; Lin, Chun-Yuan; Shih, Kuei-Chung; Huang, Jui-Wen; Tang, Chuan-Yi

    2013-12-01

    Damage to DNA is caused by ionizing radiation, genotoxic chemicals or collapsed replication forks. When DNA is damaged or cells fail to respond, a mutation that is associated with breast or ovarian cancer may occur. Mammalian cells control and stabilize the genome using a cell cycle checkpoint to prevent damage to DNA or to repair damaged DNA. Checkpoint kinase 2 (Chk2) is one of the important kinases, which strongly affects DNA-damage and plays an important role in the response to the breakage of DNA double-strands and related lesions. Therefore, this study concerns Chk2. Its purpose is to find potential inhibitors using the pharmacophore hypotheses (PhModels) and virtual screening techniques. PhModels can identify inhibitors with high biological activities and virtual screening techniques are used to screen the database of the National Cancer Institute (NCI) to retrieve compounds that exhibit all of the pharmacophoric features of potential inhibitors with high interaction energy. Ten PhModels were generated using the HypoGen best algorithm. The established PhModel, Hypo01, was evaluated by performing a cost function analysis of its correlation coefficient (r), root mean square deviation (RMSD), cost difference, and configuration cost, with the values 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer's cross-validation test for the Hypo01 model yielded a 95% confidence level, and the correlation coefficient of the testing set (rtest) had a best value of 0.81. The potential inhibitors were then chosen from the NCI database by Hypo01 model screening and molecular docking using the cdocker docking program. Finally, the selected compounds exhibited the identified pharmacophoric features and had a high interaction energy between the ligand and the receptor. Eighty-three potential inhibitors for Chk2 are retrieved for further study.

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

    PubMed

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

    2015-05-29

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

  6. 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

  7. Combined multi-pharmacophore, molecular docking and molecular dynamic study for discovery of promising MTH1 inhibitors

    NASA Astrophysics Data System (ADS)

    Dai, Duoqian; Zhou, Lu; Zhu, Xiaohong; You, Rong; Zhong, Liangliang

    2017-06-01

    MutT homolog 1 (MTH1), a nudix phosphohydrolase enzyme participates in the process of repairing of DNA damage by hydrolyzing oxidized deoxy-ribonucleoside triphosphate in cancer cells, is regarded as a potential target for anticancer therapy. In order to seek for promising inhibitor of MTH1, structured-based pharmacophore and 3D-QSAR pharmacophore hypotheses combine with the ADMET analysis and Lipinski's rule of five were used for screening the public molecules libraries (Asinex, Ibscreen and Natural). Then molecular docking studies were performed on screened hits via various docking programs (Glide SP, GOLD and Glide XP), five molecules with three scaffolds were picked out as potential inhibitors against MTH1. Eventually, 20 ns molecular dynamics simulation was implemented on the potential inhibitors. The RMSD (Root Mean Square Deviation) values were used to illustrate bind stability between potential molecules and MTH1. Therefore, the five hits may be considered as promising MTH1 inhibitors by all above studies.

  8. Homology modeling, docking and structure-based pharmacophore of inhibitors of DNA methyltransferase

    NASA Astrophysics Data System (ADS)

    Yoo, Jakyung; Medina-Franco, José L.

    2011-06-01

    DNA methyltransferase 1 (DNMT1) is an emerging epigenetic target for the treatment of cancer and other diseases. To date, several inhibitors from different structural classes have been published. In this work, we report a comprehensive molecular modeling study of 14 established DNTM1 inhibitors with a herein developed homology model of the catalytic domain of human DNTM1. The geometry of the homology model was in agreement with the proposed mechanism of DNA methylation. Docking results revealed that all inhibitors studied in this work have hydrogen bond interactions with a glutamic acid and arginine residues that play a central role in the mechanism of cytosine DNA methylation. The binding models of compounds such as curcumin and parthenolide suggest that these natural products are covalent blockers of the catalytic site. A pharmacophore model was also developed for all DNMT1 inhibitors considered in this work using the most favorable binding conformations and energetic terms of the docked poses. To the best of our knowledge, this is the first pharmacophore model proposed for compounds with inhibitory activity of DNMT1. The results presented in this work represent a conceptual advance for understanding the protein-ligand interactions and mechanism of action of DNMT1 inhibitors. The insights obtained in this work can be used for the structure-based design and virtual screening for novel inhibitors targeting DNMT1.

  9. Identification of potential CCR5 inhibitors through pharmacophore-based virtual screening, molecular dynamics simulation and binding free energy analysis.

    PubMed

    Wang, Juan; Shu, Mao; Wang, Yuanqiang; Hu, Yong; Wang, Yuanliang; Luo, Yanfeng; Lin, Zhihua

    2016-10-18

    CC chemokine receptor 5 (CCR5), a member of G protein-coupled receptors (GPCRs), plays a vital role in inflammatory responses to infection. Alterations in the expression of CCR5 have been correlated with disease progression in many types of cancers. The idea of using CCR5 as a target for therapeutic intervention has been demonstrated to prevent disease progression. To date, only a few compounds have been reported as CCR5 inhibitors. In this study, a series of CCR5 antagonists were used to construct pharmacophore models. Then the optimal model was utilized as a 3D query to identify novel chemical entities from structural databases. After refinement by molecular docking, drug-likeness analysis, molecular dynamics simulations (MDS) and binding free energy analysis, three potential inhibitors (25, 29 and 45) were identified. MD simulations suggested that the screened compounds retained the important common binding mode known for CCR5 inhibitors (maraviroc and nifeviroc), which occupied the bottom of a pocket and stabilized the conformation of CCR5. During the binding process, van der Waals interactions provided the substantial driving force. The most favorable contributions were from Tyr37, Trp86, Tyr89, Tyr108, Phe109, Phe112, Gln194, Thr195, Ile198, Trp248, Tyr251, Leu255, Thr259, Met279, Glu283 and Met287. The above results suggest that the hybrid strategy would provide a basis for rational drug design.

  10. 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.

  11. 3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors.

    PubMed

    Xie, Huiding; Qiu, Kaixiong; Xie, Xiaoguang

    2014-11-14

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

  12. 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

  13. 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

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

    PubMed

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

    2013-01-01

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

  15. Molecular Docking Study Based on Pharmacophore Modeling for Novel PhosphodiesteraseIV Inhibitors.

    PubMed

    Çifci, Gülşah; Aviyente, Viktorya; Akten, E Demet

    2012-07-01

    In this study, pharmacophore modelling was carried out for novel PhosphodiesteraseIV (PDEIV) inhibitors. A pharmacophore-based virtual screening, which resulted in 1959 hit compounds was performed with six chemical databases. The pharmacophore screening was proven to be successful in discriminating active and inactive inhibitors using a set of compounds with known activity obtained from ChEMBL database. Furthermore, the Lipinski's rule of five was applied for physicochemical filtering of the hit molecules and this yielded 1840 compounds. Three docking software tools, AutoDock 4.0, AutoDock Vina, and Gold v5.1 were used for the docking process. All 1840 compounds and the known selective inhibitor, rolipram, were docked into the active site of the target protein. A total of 234 compounds with all three scoring values higher than those of rolipram were determined with the three docking tools. The interaction maps of 14 potent inhibitors complexed with PDEIV B and D isoforms have been analyzed and seven key residues (Asn 395, Gln 443, Tyr 233, Ile 410, Phe 446, Asp 392, Thr 407) were found to interact with more than 80 % of the potent inhibitors. For each one of the 234 hit compounds, using the bound conformation with the highest AutoDock score, the interacting residues were determined. 117 out of 234 compounds are found to interact with at least five of the seven key residues and these were selected for further evaluation. The conformation with the highest AutoDock score for each 117 compounds were rescored using the DSX scoring function. This yielded a total of 101 compounds with better score values than the natural ligand rolipram. For ADME/TOX calculations, the FAF-Drugs2 server was used and 32 out of 101 compounds were found to be non-toxic.

  16. Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

    NASA Astrophysics Data System (ADS)

    Cosentino, U.; Moro, G.; Pitea, D.; Scolastico, S.; Todeschini, R.; Scolastico, C.

    1992-02-01

    A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.

  17. 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.

  18. 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.

  19. 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.

  20. 3D-pharmacophore identification for kappa-opioid agonists using ligand-based drug-design techniques.

    PubMed

    Yamaotsu, Noriyuki; Hirono, Shuichi

    2011-01-01

    A selective kappa-opioid receptor (KOR) agonist might act as a powerful analgesic without the side effects of micro-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 kappa-opioid agonists and propose a new three-dimensional pharmacophore model that encompasses the kappa-activities of all classes. This utilizes conformational sampling of agonists by high-temperature molecular dynamics and pharmacophore extraction through a series of molecular superpositions.

  1. A uniform molecular model of δ opioid agonist and antagonist pharmacophore conformations

    NASA Astrophysics Data System (ADS)

    Brandt, Wolfgang

    1998-11-01

    On the basis of a model of the pharmacophore conformations of agonist of the δ-opioid receptor the corresponding δ-antagonist conformations were determined by means of force field calculations. The results explain the unusual behavior of several cyclic β-casomorphin analogues on the molecular level. Thus, for instance, the model helps to understand why Tyr-c[D-Orn-2-Nal-D-Pro-Gly] is a mixed μ-agonist and δ-antagonist. Furthermore, the model is consistent with low energy conformations of other δ-antagonists such as Tyr-Tic-Phe, Tyr-Tic-Phe-Phe, naltrindole and BNTX. The occupation of a special spatial area by bulky groups close to the protonated N-terminus of opioid peptides is assumed to be highly critical for the switch from agonist to antagonist behavior.

  2. 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.

  3. Isoxazole analogues bind the System xc− Transporter: Structure-activity Relationship and Pharmacophore Model

    PubMed Central

    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.

    2009-01-01

    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-(CF3)2, which both inhibited glutamate up-take 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. PMID:19932968

  4. 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

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

    PubMed

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

    2015-04-01

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

  6. Development of novel HER2 inhibitors against gastric cancer derived from flavonoid source of Syzygium alternifolium through molecular dynamics and pharmacophore-based screening

    PubMed Central

    Babu, Tirumalasetty Muni Chandra; Rammohan, Aluru; Baki, Vijaya Bhaskar; Devi, Savita; Gunasekar, Duvvuru; Rajendra, Wudayagiri

    2016-01-01

    Continuous usage of synthetic chemotherapeutic drugs causes adverse effects, which prompted for the development of alternative therapeutics for gastric cancer from natural source. This study was carried out with a specific aim to screen gastroprotective compounds from the fruits of Syzygium alternifolium (Myrtaceae). Three flavonoids, namely, 1) 5-hydroxy-7,4′-dimethoxy-6,8-di-C-methylflavone, 2) kaempferol-3-O-β-d-glucopyranoside, and 3) kaempferol-3-O-α-l-rhamnopyranoside were isolated from the above medicinal plant by employing silica gel column chromatography and are characterized by NMR techniques. Antigastric cancer activity of these flavonoids was examined on AGS cell lines followed by cell cycle progression assay. In addition, pharmacophore-based screening and molecular dynamics of protein–ligand complex were carried out to identify potent scaffolds. The results showed that compounds 2 and 3 exhibited significant cytotoxic effect, whereas compound 1 showed moderate effect on AGS cells by inhibiting G2/M phase of cell cycle. Molecular docking analysis revealed that compound 2 has higher binding energies on human growth factor receptor-2 (HER2). The constructed pharmacophore models reveal that the compounds have more number of H-bond Acc/Don features which contribute to the inhibition of HER2 activity. By selecting these features, 34 hits were retrieved using the query compound 2. Molecular dynamic simulations (MDS) of protein–ligand complexes demonstrated conspicuous inhibition of HER2 as evidenced by dynamic trajectory analysis. Based on these results, the compound ZINC67903192 was identified as promising HER2 inhibitor against gastric cancer. The present work provides a basis for the discovery a new class of scaffolds from natural products for gastric carcinoma. PMID:27853354

  7. Development of novel HER2 inhibitors against gastric cancer derived from flavonoid source of Syzygium alternifolium through molecular dynamics and pharmacophore-based screening.

    PubMed

    Babu, Tirumalasetty Muni Chandra; Rammohan, Aluru; Baki, Vijaya Bhaskar; Devi, Savita; Gunasekar, Duvvuru; Rajendra, Wudayagiri

    2016-01-01

    Continuous usage of synthetic chemotherapeutic drugs causes adverse effects, which prompted for the development of alternative therapeutics for gastric cancer from natural source. This study was carried out with a specific aim to screen gastroprotective compounds from the fruits of Syzygium alternifolium (Myrtaceae). Three flavonoids, namely, 1) 5-hydroxy-7,4'-dimethoxy-6,8-di-C-methylflavone, 2) kaempferol-3-O-β-d-glucopyranoside, and 3) kaempferol-3-O-α-l-rhamnopyranoside were isolated from the above medicinal plant by employing silica gel column chromatography and are characterized by NMR techniques. Antigastric cancer activity of these flavonoids was examined on AGS cell lines followed by cell cycle progression assay. In addition, pharmacophore-based screening and molecular dynamics of protein-ligand complex were carried out to identify potent scaffolds. The results showed that compounds 2 and 3 exhibited significant cytotoxic effect, whereas compound 1 showed moderate effect on AGS cells by inhibiting G2/M phase of cell cycle. Molecular docking analysis revealed that compound 2 has higher binding energies on human growth factor receptor-2 (HER2). The constructed pharmacophore models reveal that the compounds have more number of H-bond Acc/Don features which contribute to the inhibition of HER2 activity. By selecting these features, 34 hits were retrieved using the query compound 2. Molecular dynamic simulations (MDS) of protein-ligand complexes demonstrated conspicuous inhibition of HER2 as evidenced by dynamic trajectory analysis. Based on these results, the compound ZINC67903192 was identified as promising HER2 inhibitor against gastric cancer. The present work provides a basis for the discovery a new class of scaffolds from natural products for gastric carcinoma.

  8. Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach.

    PubMed

    Sinha, Siddharth; Goyal, Sukriti; Somvanshi, Pallavi; Grover, Abhinav

    2016-01-01

    Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through in-vivo studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (r(2)) value of 0.6774, cross-validated correlation coefficient (q(2)) of 0.6157 and co-relation coefficient for external test set (pred_r(2)) of 0.7570. A high F-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of -10.097 and -9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free

  9. Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach

    PubMed Central

    Sinha, Siddharth; Goyal, Sukriti; Somvanshi, Pallavi; Grover, Abhinav

    2017-01-01

    Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through in-vivo studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (r2) value of 0.6774, cross-validated correlation coefficient (q2) of 0.6157 and co-relation coefficient for external test set (pred_r2) of 0.7570. A high F-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of −10.097 and −9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free

  10. Noscapinoids with anti-cancer activity against human acute lymphoblastic leukemia cells (CEM): a three dimensional chemical space pharmacophore modeling and electronic feature analysis.

    PubMed

    Naik, Pradeep K; Santoshi, Seneha; Joshi, Harish C

    2012-01-01

    We have identified a new class of microtubule-binding compounds-noscapinoids-that alter microtubule dynamics at stoichiometric concentrations without affecting tubulin polymer mass. Noscapinoids show great promise as chemotherapeutic agents for the treatment of human cancers. To investigate the structural determinants of noscapinoids responsible for anti-cancer activity, we tested 36 structurally diverse noscapinoids in human acute lymphoblastic leukemia cells (CEM). The IC(50) values of these noscapinoids vary from 1.2 to 56.0 μM. Pharmacophore models of anti-cancer activity were generated that identify two hydrogen bond acceptors, two aromatic rings, two hydrophobic groups, and one positively charged group as essential structural features. Additionally, an atom-based quantitative structure-activity relationship (QSAR) model was developed that gave a statistically satisfying result (R(2) = 0.912, Q(2) = 0.908, Pearson R = 0.951) and effectively predicts the anti-cancer activity of training and test set compounds. The pharmacophore model presented here is well supported by electronic property analysis using density functional theory at B3LYP/3-21*G level. Molecular electrostatic potential, particularly localization of negative potential near oxygen atoms of the dimethoxy isobenzofuranone ring of active compounds, matched the hydrogen bond acceptor feature of the generated pharmacophore. Our results further reveal that all active compounds have smaller lowest unoccupied molecular orbital (LUMO) energies concentrated over the dimethoxy isobenzofuranone ring, azido group, and nitro group, which is indicative of the electron acceptor capacity of the compounds. Results obtained from this study will be useful in the efficient design and development of more active noscapinoids.

  11. Structure based design, synthesis, pharmacophore modeling, virtual screening, and molecular docking studies for identification of novel cyclophilin D inhibitors.

    PubMed

    Valasani, Koteswara Rao; Vangavaragu, Jhansi Rani; Day, Victor W; Yan, Shirley ShiDu

    2014-03-24

    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 hopefully

  12. 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

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

    PubMed Central

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

    2015-01-01

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

  14. First pharmacophore model of CCR3 receptor antagonists and its homology model-assisted, stepwise virtual screening.

    PubMed

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

    2011-05-01

    CCR3, a G protein-coupled receptor, plays a central role in allergic inflammation and is an important drug target for inflammatory diseases. To understand the structure-function relationship of CCR3 receptor, different computational techniques were employed, which mainly include: (i) homology modeling of CCR3 receptor, (ii) 3D-quantitative pharmacophore model of CCR3 antagonists, (iii) virtual screening of small compound databases, and (iv) finally, molecular docking at the binding site of the CCR3 receptor homology model. Pharmacophore model was developed for the first time, on a training data set of 22 CCR3 antagonists, using CATALYST HypoRefine program. Best hypothesis (Hypo1) has three different chemical features: two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic. Hypo1 model was further validated using (i) 87 test set CCR3 antagonists, (ii) Cat Scramble randomization technique, and (iii) Decoy data set. Molecular docking studies were performed on modeled CCR3 receptor using 303 virtually screened hits, obtained from small compound database virtual screening. Finally, five hits were identified as potential leads against CCR3 receptor, which exhibited good estimated activities, favorable binding interactions, and high docking scores. These studies provided useful information on the structurally vital residues of CCR3 receptor involved in the antagonist binding, and their unexplored potential for the future development of potent CCR3 receptor antagonists.

  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 and conformational analysis in the gas phase and in aqueous solution of regioisomeric melatonin analogs. A theoretical and experimental study

    NASA Astrophysics Data System (ADS)

    Mendoza-Figueroa, Humberto; Martínez-Gudiño, Gelacio; Villanueva-Luna, Jorge E.; Trujillo-Serrato, Joel J.; Morales-Ríos, Martha S.

    2017-04-01

    In this work, 2-(N-acylaminoalkyl)indoles 1a-1d, that incorporate a pMeOBn group at the 3-position of the indole ring were virtual screened as potential melatoninergic ligands by analog-based design study using pharmacophore modeling. Pharmacophore models for melatoninergic agonist and antagonist activity were developed in order to identify the molecular constraints that define the geometric relationship among chemical features in each model. The best hypothesis consisted of six features for agonists and eight features for antagonists. The models suggest that the agonists and antagonists can share the same 3D arrangement for the six common pharmacophoric elements identified: two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), one hydrophobic area (H), and two aromatic rings (AR). The extra hydrofobic interaction might be used as criterion for identified the pharmacological antagonist profile. Based on the pharmacophore fit, it was found that structures 1c and 1d show a good structural overlay that meets the requirements for the antagonistic pharmacophore hypothesis. Molecular modeling studies using the PCM solvation model predicted that the most stable conformers of 1a-1d match the antagonist pharmacophore hypothesis in contrast to those in the gas phase. Structures 1a-1c were synthesized only but the activities were not tested.

  17. 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

  18. Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors.

    PubMed

    Reddy, Karnati Konda; Singh, Sanjeev Kumar; Dessalew, Nigus; Tripathi, Sunil Kumar; Selvaraj, Chandrabose

    2012-06-01

    Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to N-methyl pyrimidones as HIV-1 integrase inhibitors. Based on the ligand-based pharmacophore model, we got 5-point pharmacophore model AADDR, with two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R). The generated pharmacophore-based alignment was used to derive a predictive atom-based 3D-QSAR model for the training set (r(2) = 0.92, SD = 0.16, F = 84.8, N = 40) and for test set (Q(2) = 0.71, RMSE = 0.06, Pearson R = 0.90, N = 10). From these results, AADDR pharmacophore feature was selected as best common pharmacophore hypothesis, and atom-based 3D-QSAR results also support the outcome by means of favourable and unfavourable regions of hydrophobic and electron-withdrawing groups for the most potent compound 30. These results can be useful for further design of new and potent HIV-1 IN inhibitors.

  19. Pharmacophore modeling and three-dimensional database searching for drug design using catalyst.

    PubMed

    Kurogi, Y; Güner, O F

    2001-07-01

    Perceiving a pharmacophore is the first essential step towards understanding the interaction between a receptor and a ligand. Once a pharmacophore is established, a beneficial use of it is 3D database searching to retrieve novel compounds that would match the pharmacophore, without necessarily duplicating the topological features of known active compounds (hence remain independent of existing patents). As the 3D searching technology has evolved over the years, it has been effectively used for lead optimization, combinatorial library focusing, as well as virtual high-throughput screening. Clearly established as one of the successful computational tools in rational drug design, we present in this review article a brief history of the evolution of this technology and detailed algorithms of Catalyst, the latest 3D searching software to be released. We also provide brief summary of published successes with this technology, including two recent patent applications.

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

    PubMed

    Miller, Bill R; Roitberg, Adrian E

    2013-09-01

    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. Copyright © 2013 Elsevier Inc. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  2. Identification of dual kinase inhibitors of CK2 and GSK3β: combined qualitative and quantitative pharmacophore modeling approach.

    PubMed

    Pardhi, Triveni; Vasu, Kamala

    2017-02-07

    PTEN, a tumor suppressor protein, gets deactivated by casein kinase 2 (CK2) and glycogen synthase kinase 3β (GSK3β), which are the major causes of PI3K/AKT-driven tumors. To surmount this problem, the multi-target inhibitor strategy may be of great significance. The goal of this study was to design dual-target inhibitors of CK2 and GSK3β using a combination of pharmacophore modeling and molecular docking studies. The common feature-based (qualitative) and 3DQSAR-based (quantitative) pharmacophore models were generated and validated. The best pharmacophore models (Pharm18 and Hypo1) comprised two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic features. The models were used to screen various chemical database and top mapped compounds from each database were selected. They were processed for Lipinski filter, Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis, and docking studies. We have obtained six hits with comparable dock score to the reported inhibitors. We have concluded Hit15 as a competent candidate based on its docking and Density Functional Theory (DFT) calculations. It showed 140.73 and 130.79 dock score in CK2 and GSK3β, respectively. The electronic property of Hit 15 showed the lowest energy gap (0.021) compared to other hits and active ligands which suggest its higher reactivity. In conclusion, this study may assist in the development of new potent dual kinase inhibitors of CK2 and GSK3β. Also, the overture effort of combined qualitative and quantitative modeling for the development of multi-target inhibitors may support the future endeavors.

  3. Generation of pharmacophore and atom based 3D-QSAR model of novel isoquinolin-1-one and quinazolin-4-one-type inhibitors of TNFα.

    PubMed

    Hanumanthappa, Pradeep; Teli, Mahesh K; Krishnamurthy, Rajanikant G

    2012-05-01

    In the present report, 3D-QSAR analysis was executed on the previously synthesized and evaluated derivatives of isoquinolin-1-ones and quinazolin-4-ones; potent inhibitors of tumor necrosis factor α (TNFα). Statistically significant 3D-QSAR models were generated using 42 molecules in the training set. The predictive ability of models was determined using a randomly chosen test set of 16 molecules, which gave excellent predictive correlation coefficients for 3-D models, suggesting good predictive index. Pharmacophore prediction generated a five point pharmacophore (AAHRR): two hydrogen bond acceptor (A), one hydrophobic (H) and two ring (RR) features. This pharmacophore hypothesis furnished a statistically meaningful 3D-QSAR model with partial least-square (PLS) factors seven having R2=0.9965, Q2=0.6185, Root Mean Squared Error=0.4284 and Pearson-R=0.853. Docking study revealed the important amino acid residues (His 15, Tyr 59, Tyr 151, Gly 121 and Gly 122) in the active site of TNFα that are involved in binding of the active ligand. Orientation of the pharmacophore hypothesis AAHRR.25 corresponded very closely with the binding mode recorded in the active site of ligand bound complex. The results of ligand based pharmacophore hypothesis and atom based 3D-QSAR furnished crucial structural insights and also highlighted the important binding features of isoquinolin-1-ones and quinazolin-4-ones derivatives, which may provide guidance for the rational design of novel and more potent TNFα inhibitors.

  4. Validation of TZD Scaffold as Potential ARIs: Pharmacophore Modelling, Atom-based 3D QSAR and Docking Studies.

    PubMed

    Dahiya, Lalita; Mahapatra, Manoj Kumar; Kaur, Ramandeep; Kumar, Vipin; Kumar, Manoj

    2017-03-15

    Metabolic disorders associated with diabetic patients are a serious concern. Aldose reductase (ALR2) has been identified as first rate-limiting enzyme in the polyol pathway which catalyzes the reduction of glucose to sorbitol. It represents one of the validated targets to develop potential new chemical entities for the prevention and subsequent progression of microvascular diabetic complications. In order to further understand the intricate structural prerequisites of molecules to act as ALR2 inhibitors, ligand-based pharmacophore model, atom-based 3D-QSAR and structure based drug design studies have been performed on a series of 2,4-thiazolidinedione derivatives with ALR2 inhibitory activity. In the present study, a validated six point pharmacophore model (AAADNR) with three hydrogen bond acceptor (A), one hydrogen bond donor (D), one negative ionic group (N) and one aromatic ring (R) was developed using PHASE module of Schrodinger suite with acceptable PLS statistics (survival score = 3.871, cross-validated correlation coefficient Q2 = 0.6902, correlation coefficient of multiple determination r2 = 0.9019, Pearson-R coefficient = 0.8354 and F distribution = 196.2). In silico predictive studies (pharmacophore modeling, atom-based 3D QSAR and docking combined with drug receptor binding free energetics and pharmacokinetic drug profile) highlighted some of the important structural features of thiazolidinedione analogues required for potential ALR2 inhibitory activity. The result of these studies may account to design a legitimate template for rational drug design of novel, potent and promising ALR2 inhibitors.

  5. Pharmacophore feature-based virtual screening for finding potent GSK-3 inhibitors using molecular docking and dynamics simulations

    PubMed Central

    Chauhan, Navneet; Gajjar, Anuradha; Basha, Syed Hussain

    2016-01-01

    Glycogen synthase kinase-3 (GSK-3) is a multitasking serine/threonine protein kinase, which is associated with the pathophysiology of several diseases such as diabetes, cancer, psychiatric and neurodegenerative diseases. Tideglusib is a potent, selective, and irreversible GSK-3 inhibitor that has been investigated in phase II clinical trials for the treatment of progressive supranuclear palsy and Alzheimer's disease. In the present study, we performed pharmacophore feature-based virtual screening for identifying potent targetspecific GSK-3 inhibitors. We found 64 compounds that show better GSK-3 binding potentials compared with those of Tideglusib. We further validated the obtained binding potentials by performing 20-ns molecular dynamics simulations for GSK-3 complexed with Tideglusib and with the best compound found via virtual screening in this study. Several interesting molecular-level interactions were identified, including a covalent interaction with Cys199 residue at the entrance of the GSK-3 active site. These findings are expected to play a crucial role in the binding of target-specific GSK-3 inhibitors. PMID:28293069

  6. 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.

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

    PubMed

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

    2014-01-01

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

  8. 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.

  9. 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.

  10. In Silico Drug-Designing Studies on Flavanoids as Anticolon Cancer Agents: Pharmacophore Mapping, Molecular Docking, and Monte Carlo Method-Based QSAR Modeling.

    PubMed

    Simon, Lalitha; Imane, Abdelli; Srinivasan, K K; Pathak, Lokesh; Daoud, I

    2016-04-08

    In silico molecular modeling studies were carried out on some newly synthesized flavanoid analogues. Search for potential targets for these compounds was performed using pharmacophore-mapping algorithm employing inverse screening of some representative compounds to a large set of pharmacophore models constructed from human target proteins. Further, molecular docking studies were carried out to assess binding affinity of these compounds to proteins mediating tumor growth. In vitro anticancer studies were carried out on colon cancer cell lines (HCT116) to assess validity of this approach for target identification of the new compounds. Further important structural features of compounds for anticolon cancer activity were assessed using Monte Carlo-based SMILES and hydrogen graph-Based QSAR studies. In conclusion this study have depicted successful and stepwise application of pharmacophore mapping, molecular docking, and QSAR studies in target identification and lead optimization of flavonoids.

  11. Discovery of potential M2 channel inhibitors based on the amantadine scaffold via virtual screening and pharmacophore modeling.

    PubMed

    Tran, Linh; Choi, Sy Bing; Al-Najjar, Belal O; Yusuf, Muhammad; Wahab, Habibah A; Le, Ly

    2011-12-08

    The M2 channel protein on the influenza A virus membrane has become the main target of the anti-flu drugs amantadine and rimantadine. The structure of the M2 channel proteins of the H3N2 (PDB code 2RLF) and 2009-H1N1 (Genbank accession number GQ385383) viruses may help researchers to solve the drug-resistant problem of these two adamantane-based drugs and develop more powerful new drugs against influenza A virus. In the present study, we searched for new M2 channel inhibitors through a combination of different computational methodologies, including virtual screening with docking and pharmacophore modeling. Virtual screening was performed to calculate the free energies of binding between receptor M2 channel proteins and 200 new designed ligands. After that, pharmacophore analysis was used to identify the important M2 protein-inhibitor interactions and common features of top binding compounds with M2 channel proteins. Finally, the two most potential compounds were determined as novel leads to inhibit M2 channel proteins in both H3N2 and 2009-H1N1 influenza A virus.

  12. Development of pharmacophore models for small molecules targeting RNA: Application to the RNA repeat expansion in myotonic dystrophy type 1.

    PubMed

    Angelbello, Alicia J; González, Àlex L; Rzuczek, Suzanne G; Disney, Matthew D

    2016-12-01

    RNA is an important drug target, but current approaches to identify bioactive small molecules have been engineered primarily for protein targets. Moreover, the identification of small molecules that bind a specific RNA target with sufficient potency remains a challenge. Computer-aided drug design (CADD) and, in particular, ligand-based drug design provide a myriad of tools to identify rapidly new chemical entities for modulating a target based on previous knowledge of active compounds without relying on a ligand complex. Herein we describe pharmacophore virtual screening based on previously reported active molecules that target the toxic RNA that causes myotonic dystrophy type 1 (DM1). DM1-associated defects are caused by sequestration of muscleblind-like 1 protein (MBNL1), an alternative splicing regulator, by expanded CUG repeats (r(CUG)(exp)). Several small molecules have been found to disrupt the MBNL1-r(CUG)(exp) complex, ameliorating DM1 defects. Our pharmacophore model identified a number of potential lead compounds from which we selected 11 compounds to evaluate. Of the 11 compounds, several improved DM1 defects both in vitro and in cells.

  13. Novel butyrylcholinesterase inhibitors through pharmacophore modeling, virtual screening and DFT-based approaches along-with design of bioisosterism-based analogues.

    PubMed

    Gogoi, Dhrubajyoti; Chaliha, Amrita Kashyap; Sarma, Diganta; Kakoti, Bibhuti Bhusan; Buragohain, Alak Kumar

    2017-01-01

    Ligand and structure-based pharmacophore models were used to identify the important chemical features of butyrylcholinesterase (BChE) inhibitors. A training set of 16 known structurally diverse compounds with a wide range of inhibitory activity against BChE was used to develop a quantitative ligand-based pharmacophore (Hypo1) model to identify novel BChE inhibitors in virtual screening databases. A structure-based pharmacophore hypothesis (Phar1) was also developed with the ligand-binding site of BChE in consideration. Further, the models were validated using test set, Fisher's Randomization and Leave-one-out validation methods. Well-validated pharmacophore hypotheses were further used as 3D queries in virtual screening and 430 compounds were finally selected for molecular docking analysis. Subsequently, ADMET, DFT and chemical similarity search were employed to narrow down on seven compounds as potential drug candidates. Analogues of the best hit were further developed through a bioisosterism-guided approach to further generate a library of potential BChE inhibitors.

  14. Generation of the first structure-based pharmacophore model containing a selective "zinc binding group" feature to identify potential glyoxalase-1 inhibitors.

    PubMed

    Al-Balas, Qosay; Hassan, Mohammad; Al-Oudat, Buthina; Alzoubi, Hassan; Mhaidat, Nizar; Almaaytah, Ammar

    2012-11-22

    Within this study, a unique 3D structure-based pharmacophore model of the enzyme glyoxalase-1 (Glo-1) has been revealed. Glo-1 is considered a zinc metalloenzyme in which the inhibitor binding with zinc atom at the active site is crucial. To our knowledge, this is the first pharmacophore model that has a selective feature for a "zinc binding group" which has been customized within the structure-based pharmacophore model of Glo-1 to extract ligands that possess functional groups able to bind zinc atom solely from database screening. In addition, an extensive 2D similarity search using three diverse similarity techniques (Tanimoto, Dice, Cosine) has been performed over the commercially available "Zinc Clean Drug-Like Database" that contains around 10 million compounds to help find suitable inhibitors for this enzyme based on known inhibitors from the literature. The resultant hits were mapped over the structure based pharmacophore and the successful hits were further docked using three docking programs with different pose fitting and scoring techniques (GOLD, LibDock, CDOCKER). Nine candidates were suggested to be novel Glo-1 inhibitors containing the "zinc binding group" with the highest consensus scoring from docking.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    SciTech Connect

    Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

    2016-06-18

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

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

    SciTech Connect

    Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

    2016-06-18

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

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

    DOE PAGES

    Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

    2016-06-18

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

  19. Optimization, pharmacophore modeling and 3D-QSAR studies of sipholanes as breast cancer migration and proliferation inhibitors.

    PubMed

    Foudah, Ahmed I; Sallam, Asmaa A; Akl, Mohamed R; El Sayed, Khalid A

    2014-02-12

    Sipholenol A, a triterpene isolated from the Red Sea sponge Callyspongia siphonella, was previously shown to reverse multidrug resistance in P-glycoprotein-overexpressing cancer cells. Moreover, sipholanes showed promising in vitro inhibitory effects against the invasion and migration of the metastatic human breast cancer cell line MDA-MB-231. The breast tumor kinase (Brk), a mediator of cancer cell phenotypes important for proliferation, survival, and migration, was proposed as a potential target. This study reports additional semisynthetic optimization of sipholenol A esters to improve the breast cancer antimigratory and antiproliferative activities as well as Brk phosphorylation inhibition. Fifteen new sipholenol A analogs (25-39) were semisynthesized. Sipholenol A 4β-4',5'-dichlorobenzoate ester (29) was the most potent, with an IC50 value of 1.3 μM in the migration assay. The level of Brk phosphorylation inhibition of 29 was assessed using the Z'-LYTE™ kinase assay and Western blot analysis. Active analogs showed no toxicity on the non-tumorigenic epithelial breast cell line MCF10A at doses equal to their IC50 values or higher in migration and proliferation assays, suggesting their selectivity towards malignant cells. Pharmacophore modeling and 3D-QSAR studies were conducted to identify important pharmacophoric features and correlate 3D-chemical structure with activity. These studies provided the evidence for future design of novel antimigratory compounds based on a simplified sipholane structure possessing rings A and B (perhydrobenzoxepine) connected to substituted aromatic esters, with the elimination of rings C and D ([5,3,0]bicyclodecane system). This will enable the future synthesis of the new active entities feasibly and cost-effectively. These results demonstrate the potential of marine natural products for the discovery of novel scaffolds for the control and management of metastatic breast cancer. Copyright © 2013 Elsevier Masson SAS. All

  20. Investigation on quantitative structure activity relationships and pharmacophore modeling of a series of mGluR2 antagonists.

    PubMed

    Zhang, Meng-Qi; Zhang, Xiao-Le; Li, Yan; Fan, Wen-Jia; Wang, Yong-Hua; Hao, Ming; Zhang, Shu-Wei; Ai, Chun-Zhi

    2011-01-01

    MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson's disease and schizophrenia. Herein, we report the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [(3)H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q(2) of 0.513, R(2) (ncv) of 0.868, R(2) (pred) = 0.876, while the CoMSIA model yielded a Q(2) of 0.450, R(2) (ncv) = 0.899, R(2) (pred) = 0.735. For activity II study, CoMFA model yielded statistics of Q(2) = 0.5, R(2) (ncv) = 0.715, R(2) (pred) = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R(7), R(3) and position A benefit activity I of the antagonists, but decrease it when projected in R(8) and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity

  1. Combining pharmacophore search, automated docking, and molecular dynamics simulations as a novel strategy for flexible docking. Proof of concept: docking of arginine-glycine-aspartic acid-like compounds into the alphavbeta3 binding site.

    PubMed

    Moitessier, Nicolas; Henry, Christophe; Maigret, Bernard; Chapleur, Yves

    2004-08-12

    A novel and highly efficient flexible docking approach is presented where the conformations (internal degrees of freedom) and orientations (external degrees of freedom) of the ligands are successively considered. This hybrid method takes advantage of the synergistic effects of structure-based and ligand-based drug design techniques. Preliminary antagonist-derived pharmacophore determination provides the postulated bioactive conformation. Subsequent docking of this pharmacophore to the receptor crystal structure results in a postulated pharmacophore/receptor binding mode. Pharmacophore-oriented docking of antagonists is subsequently achieved by matching ligand interacting groups with pharmacophore points. Molecular dynamics in water refines the proposed complexes. To validate the method, arginine-glycine-aspartic acid (RGD) containing peptides, pseudopeptides, and RGD-like antagonists were docked to the crystal structure of alphavbeta3 holoprotein and apoprotein. The proposed directed docking was found to be more accurate, faster, and less biased with respect to the protein structure (holo and apoprotein) than DOCK, Autodock, and FlexX docking methods. The successful docking of an antagonist recently cocrystallized with the receptor to both apo and holoprotein is particularly appealing. The results summarized in this report illustrated the efficiency of our light CoMFA/rigid body docking hybrid method.

  2. Computer-assisted determination of minimum energy conformations. 7: A pharmacophore model of the active region of the alpha2-adrenoceptor

    NASA Astrophysics Data System (ADS)

    Ashman, William P.; Mickiewicz, A. P.; Nelson, Todd M.

    1992-09-01

    Molecular modeling and computational chemistry techniques are used to analyze compounds in developing pharmacophores of biological receptors to use as templates in structure activity relationship studies and to design new chemicals having physiological activity of interest. In this study, the results of x-ray crystal analyses and PM3 semi-empirical molecular orbital conformational analyses are used to determine the three-dimensional representations of selected adrenergic compounds known to be agonists with the alpha2-adrenoceptor in achieving optimized geometries and electrostatic parameters. The alpha2-adrenergic agonists interact with the adrenergic system receptors to produce various increases or decreases in hemodynamic responses (i.e., hypertension, hypotension, and bradycardia) and sedation. A pharmacophore model of the active region of the alpha2-adrenoceptor is described based on the superimposition of common structural, electrostatic, and physicochemical features of the compounds. Using the model to predict compound adrenergic activity and to design alpha2-adrenergic compounds is discussed.

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

    PubMed

    Sindhu, Thangaraj; Srinivasan, Pappu

    2014-08-01

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

  4. Pharmacophore modeling, 3D-QSAR, and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents.

    PubMed

    Malik, Ruchi; Mehta, Pakhuri; Srivastava, Shubham; Choudhary, Bhanwar Singh; Sharma, Manish

    2017-06-01

    Biological mechanism attributing mutations in KCNQ2/Q3 results in benign familial neonatal epilepsy (BFNE), a rare form of epilepsy and thus neglected. It offers a potential target for antiepileptic drug discovery. In the present work, a pharmacophore-based 3D-QSAR model was generated for a series of N-pyridyl and pyrimidine benzamides possessing KCNQ2/Q3 opening activity. The pharmacophore model generated contains one hydrogen bond donor (D), one hydrophobic (H), and two aromatic rings (R). They are the crucial molecular write-up detailing predicted binding efficacy of high affinity and low affinity ligands for KCNQ2/Q3 opening activity. Furthermore, it has been validated by using a biological correlation between pharmacophore hypothesis-based 3D-QSAR variables and functional fingerprints of openers responsible for the receptor binding and also by docking of these benzamides into the validated homology model. Excellent statistical computational tools of QSAR model such as good correlation coefficient (R(2 )>( )0.80), higher F value (F > 39), and excellent predictive power (Q(2) > 0.7) with low standard deviation (SD <0.3) strongly suggest that the developed model could be used for prediction of antiepileptic activity of newer analogs. A preliminary pharmacokinetic profile of these derivatives was also performed on the basis of QikProp predictions.

  5. Revision of the classical dopamine D2 agonist pharmacophore based on an integrated medicinal chemistry, homology modelling and computational docking approach.

    PubMed

    Krogsgaard-Larsen, N; Harpsøe, K; Kehler, J; Christoffersen, C T; Brøsen, P; Balle, T

    2014-10-01

    The scientific advances during the 1970ies and 1980ies within the field of dopaminergic neurotransmission enabled the development of a pharmacophore that became the template for design and synthesis of dopamine D2 agonists during the following four decades. A major drawback, however, is that this model fails to accommodate certain classes of restrained dopamine D2 agonists including ergoline structures. To accommodate these, a revision of the original model was required. The present study has addressed this by an extension of the original model without compromising its obvious qualities. The revised pharmacophore contains an additional hydrogen bond donor feature, which is required for it to accommodate ergoline structures in a low energy conformation and in accordance with the steric restrictions dictated by the original model. The additional pharmacophore feature suggests ambiguity in the binding mode for certain compounds, including a series of ergoline analogues, which was reported recently. The ambiguity was confirmed by docking to a homology model of the D2 receptor as well as by pharmacological characterization of individual enantiomers of one of the analogues. The present research also addresses the potential of designing ligands that interact with the receptor in a large, distal cavity of the dopamine D2 receptor that has not previously been studied systematically. The pharmacological data indicate that this area may be a major determinant for both the dopamine D2 affinity and efficacy, which remains to be explored in future studies.

  6. Pharmacophore modeling, resistant mutant isolation, docking, and MM-PBSA analysis: Combined experimental/computer-assisted approaches to identify new inhibitors of the bovine viral diarrhea virus (BVDV).

    PubMed

    Tonelli, Michele; Boido, Vito; La Colla, Paolo; Loddo, Roberta; Posocco, Paola; Paneni, Maria Silvia; Fermeglia, Maurizio; Pricl, Sabrina

    2010-03-15

    Starting from a series of our new 2-phenylbenzimidazole derivatives, shown to be selectively and potently active against the bovine viral diarrhea virus (BVDV), we developed a hierarchical combined experimental/molecular modeling strategy to explore the drug leads for the BVDV RNA-dependent RNA-polymerase. Accordingly, a successful 3D pharmacophore model was developed, characterized by distinct chemical features that may be responsible for the activity of the inhibitors. BVDV mutants resistant to lead compounds in our series were then isolated, and the mutant residues on the viral molecular target, the RNA-dependent RNA-polymerase, were identified. Docking procedures upon pharmacophoric constraints and mutational data were carried out, and the binding affinity of all active compounds for the RdRp were estimated. Given the excellent agreement between in silico and in vitro data, this procedure is currently being employed in the design a new series of more selective and potent BVDV inhibitors.

  7. Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

    NASA Astrophysics Data System (ADS)

    Gao, Qi; Wang, Yijun; Hou, Jiaying; Yao, Qizheng; Zhang, Ji

    2017-07-01

    Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1' pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC50 value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.

  8. Discovery of high-affinity ligands of sigma1 receptor, ERG2, and emopamil binding protein by pharmacophore modeling and virtual screening.

    PubMed

    Laggner, Christian; Schieferer, Claudia; Fiechtner, Birgit; Poles, Gloria; Hoffmann, Rémy D; Glossmann, Hartmut; Langer, Thierry; Moebius, Fabian F

    2005-07-28

    ERG2, emopamil binding protein (EBP), and sigma-1 receptor (sigma(1)) are enzymes of sterol metabolism and an enzyme-related protein, respectively, that share high affinity for various structurally diverse compounds. To discover novel high-affinity ligands, pharmacophore models were built with Catalyst based upon a series of 23 structurally diverse chemicals exhibiting K(i) values from 10 pM to 100 microM for all three proteins. In virtual screening experiments, we retrieved drugs that were previously reported to bind to one or several of these proteins and also tested 11 new hits experimentally, of which three, among them raloxifene, had affinities for sigma(1) or EBP of <60 nM. When used to search a database of 3525 biochemicals of intermediary metabolism, a slightly modified ERG2 pharmacophore model successfully retrieved 10 substrate candidates among the top 28 hits. Our results indicate that inhibitor-based pharmacophore models for sigma(1), ERG2, and EBP can be used to screen drug and metabolite databases for chemically diverse compounds and putative endogenous ligands.

  9. Analysis of positions and substituents on genotoxicity of fluoroquinolones with quantitative structure-activity relationship and 3D Pharmacophore model.

    PubMed

    Fengxian, Chen; Reti, Hai

    2017-02-01

    The genotoxicity values of 21 quinolones were studied to establish a quantitative structure-activity relationship model and 3D Pharmacophore model separately for screening essential positions and substituents that contribute to genotoxicity of fluoroquinolones (FQs). A full factor experimental design was performed to analyze the specific main effect and second-order interaction effect of different positions and substituents on genotoxicity, forming a reasonable modification scheme which was validated on typical FQ with genotoxicity and efficacy data. Four positions (1, 5, 7, 8) were screened finally to form the full factorial experimental design which contained 72 congeners in total, illustrating that: the dominant effect of 5 and 7-positions on genotoxicity of FQs is main effect; meanwhile the effect of 1 and 8-positions is a second-order interaction effect; two adjacent positions always have stronger second-order interaction effect and lower genotoxicity; the obtained modification scheme had been validated on typical FQ congeners with the modified compound has a lower genotoxicity, higher synthesis feasibilities and efficacy.

  10. 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

  11. Combined use of pharmacophoric models together with drug metabolism and genotoxicity "in silico" studies in the hit finding process

    NASA Astrophysics Data System (ADS)

    Jerez, Ma José; Jerez, Miguel; González-García, Coral; Ballester, Sara; Castro, Ana

    2013-01-01

    In this study we propose a virtual screening strategy based on the generation of a pharmacophore hypothesis, followed by an in silico evaluation of some ADME-TOX properties with the aim to apply it to the hit finding process and, specifically, to characterize new chemical entities with potential to control inflammatory processes mediated by T lymphocytes such as multiple sclerosis, systemic lupus erithematosus or rheumatoid arthritis. As a result, three compounds with completely novel scaffolds were selected as final hits for future hit-to-lead optimization due to their anti-inflammatory profile. The biological results showed that the selected compounds increased the intracellular cAMP levels and inhibited cell proliferation in T lymphocytes. Moreover, two of these compounds were able to increase the production of IL-4, an immunoregulatory cytokine involved in the selective deviation of T helper (Th) immune response Th type 2 (Th2), which has been proved to have anti-inflammatory properties in several animal models for autoimmune pathologies as multiple sclerosis or rheumatoid arthritis. Thus our pharmacological strategy has shown to be useful to find molecules with biological activity to control immune responses involved in many inflammatory disorders. Such promising data suggested that this in silico strategy might be useful as hit finding process for future drug development.

  12. 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

  13. Investigation on Quantitative Structure Activity Relationships and Pharmacophore Modeling of a Series of mGluR2 Antagonists

    PubMed Central

    Zhang, Meng-Qi; Zhang, Xiao-Le; Li, Yan; Fan, Wen-Jia; Wang, Yong-Hua; Hao, Ming; Zhang, Shu-Wei; Ai, Chun-Zhi

    2011-01-01

    MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson’s disease and schizophrenia. Herein, we report the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [3H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q2 of 0.513, R2 ncv of 0.868, R2 pred = 0.876, while the CoMSIA model yielded a Q2 of 0.450, R2 ncv = 0.899, R2 pred = 0.735. For activity II study, CoMFA model yielded statistics of Q2 = 0.5, R2 ncv = 0.715, R2 pred = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R7, R3 and position A benefit activity I of the antagonists, but decrease it when projected in R8 and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3

  14. Rational design, synthesis, pharmacophore modeling, and docking studies for identification of novel potent DNA-PK inhibitors.

    PubMed

    Ihmaid, Saleh; Ahmed, Hany E A; Al-Sheikh Ali, Adeeb; Sherif, Yousery E; Tarazi, Hamadeh M; Riyadh, Sayed M; Zayed, Mohamed F; Abulkhair, Hamada S; Rateb, Heba S

    2017-06-01

    Drugs of cancer based upon ionizing radiation or chemotherapeutic treatment may affect breaking of DNA double strand in cell. DNA-PK enzyme has emerged as an attractive target for drug discovery efforts toward DNA repair pathways. Hence, the search for potent and selective DNA-PK inhibitors has particularly considered state-of-the art and several series of inhibitors have been designed. In this article, a novel benchmark DNA-PK database of 43 compounds was built and described. Ligand-based approaches including pharmacophore and QSAR modeling were applied and novel models were introduced and analyzed for predicting activity test for DNA-PK drug candidates. Based upon the modeling results, we gave a report of synthesis of fifteen novel 2-((8-methyl-2-morpholino-4-oxo-4H-benzo[e][1,3]oxazin-7-yl)oxy)acetamide derivatives and in vitro evaluation for DNA-PK inhibitory and antiproliferative activities. These fifteen compounds overall are satisfied with Lipinski's rule of five. The biological testing of target compounds showed five promising active compounds 7c, 7d, 7f, 9e and 9f with micromolar DNA-PK activity range from 0.25 to 5µM. In addition, SAR of the compounds activity was investigated and confirmed that the terminal aryl moiety was found to be quite crucial for DNA-PK activity. Moreover flexible docking simulation was done for the potent compounds into the putative binding site of the 3D homology model of DNA-PK enzyme and the probable interaction model between DNA-PK and the ligands was investigated and interpreted. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. 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

  16. Pharmacophore-based similarity scoring for DOCK.

    PubMed

    Jiang, Lingling; Rizzo, Robert C

    2015-01-22

    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.

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

    PubMed

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

    2017-01-01

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

  18. In silico pharmacophore modeling on known pyridinium oxime reactivators of cyclosarin (GF) inhibited AChE to Aid discovery of potential, more efficacious novel non-oxime reactivators.

    PubMed

    Bhattacharjee, Apurba K; Musilek, Kamil; Kuca, Kamil

    2013-09-01

    Cyclohexyl methylphosphonofluoridate (cyclosarin, cyclosin, GF) is a highly toxic organophosphorus (OP) nerve agent considered as potential warfare threats and known to be resistant to conventional oxime antidotal therapy. To aid discovery of novel antidotes for GF toxicity, a three-dimensional in silico pharmacophore model for reactivation efficacy against GF intoxication is presented. The model was generated from published experimental percentage reactivation data on oximes as changes of AChE/BuChE activities in the whole blood after cyclosarin intoxication and administration. The generated pharmacophore model was found to contain a hydrogen bond donor site and two ring aromatic sites as necessary optimal features for reactivation of GF intoxication. Stereo-electronic features of oximes reported by us earlier provided guidance to develop the model and were found to be consistent with the reported structure activity data. Furthermore, from virtual screening of two commercial databases, Maybridge and ChemNavigator using map-fitting of the model led us to identify two new non-oxime compounds showing reactivation efficacy within 10-fold range of 2-PAM for DFP-inhibited AChE. Since GF is a G simulator like DFP (diisopropylfluorophosphate), the model should have the potential for discovery of novel reactivators against GF intoxication.

  19. 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

  20. 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

  1. 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.

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

    PubMed

    Ugale, V G; Bari, S B

    2016-01-01

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

  3. Ligand-based and e-pharmacophore modeling, 3D-QSAR and hierarchical virtual screening to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3).

    PubMed

    Kaur, Maninder; Silakari, Om

    2016-11-11

    The clinical efficacy of multiple kinase inhibitors has caught the interest of Pharmaceutical and Biotech researchers to develop potential drugs with multi-kinase inhibitory activity for complex diseases. In the present work, we attempted to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3), keys players in immune signaling, by developing ideal pharmacophores integrating Ligand-based pharmacophore models (LBPMs) and Structure-based pharmacophore models (SBPMs), thereby projecting the optimum pharmacophoric required for inhibition of both the kinases. The four point LBPM; ADPR.14 suggested the presence of one hydrogen bond acceptor, one hydrogen bond donor, one positive ionizable, and one ring aromatic feature for Syk inhibitory activity and AADH.54 proposed the necessity of two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature for JAK3 inhibitory activity. To our interest, SBPMs identified additional ring aromatic features required for inhibition of both the kinases. For Syk inhibitory activity, the hydrogen bond acceptor feature indicated by LBPM was devoid of forming hydrogen bonding interaction with the hinge region amino acid residue (Ala451). Thus merging the information revealed by both LBPMs and SBPMs, ideal pharmacophore models i.e. ADPRR.14 (Syk) and AADHR.54 (JAK3) were generated. These models after rigorous statistical validation were used for screening of Asinex database. The systematic virtual screening protocol, including pharmacophore and docking-based screening, ADME property, and MM-GBSA energy calculations, retrieved final 10 hits as dual inhibitors of Syk and JAK3. Final 10 hits thus obtained can aid in the development of potential therapeutic agents for autoimmune disorders. Also the top two hits were evaluated against both the enzymes.

  4. Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining

    PubMed Central

    Haidar, Samer; Bouaziz, Zouhair; Marminon, Christelle; Laitinen, Tuomo; Poso, Antti; Le Borgne, Marc; Jose, Joachim

    2017-01-01

    Protein kinase CK2, initially designated as casein kinase 2, is an ubiquitously expressed serine/threonine kinase. This enzyme, implicated in many cellular processes, is highly expressed and active in many tumor cells. A large number of compounds has been developed as inhibitors comprising different backbones. Beside others, structures with an indeno[1,2-b]indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors of human protein kinase CK2, we report here on the generation of common feature pharmacophore model to further explain the binding requirements for human CK2 inhibitors. Nine common chemical features of indeno[1,2-b]indole-type CK2 inhibitors were determined using MOE software (Chemical Computing Group, Montreal, Canada). This pharmacophore model was used for database mining with the aim to identify novel scaffolds for developing new potent and selective CK2 inhibitors. Using this strategy several structures were selected by searching inside the ZINC compound database. One of the selected compounds was bikaverin (6,11-dihydroxy-3,8-dimethoxy-1-methylbenzo[b]xanthene-7,10,12-trione), a natural compound which is produced by several kinds of fungi. This compound was tested on human recombinant CK2 and turned out to be an active inhibitor with an IC50 value of 1.24 µM. PMID:28075359

  5. Homology modelling, docking, pharmacophore and site directed mutagenesis analysis to identify the critical amino acid residue of PknI from Mycobacterium tuberculosis.

    PubMed

    Kandasamy, Srinivasan; Hassan, Sameer; Gopalaswamy, Radha; Narayanan, Sujatha

    2014-07-01

    Tuberculosis is caused by Mycobacterium tuberculosis, an intracellular pathogen. PknI is one of the 11 functional Serine/Threonine Protein Kinases which is predicted to regulate the cell division of M. tuberculosis. In order to find newer drugs and vaccine we need to understand the pathogenesis of the disease. We have used the bioinformatics approach to identify the functionally active residues of PknI and to confirm the same with wet lab experiments. In the current study, we have created homology model for PknI and have done comparative structural analysis of PknI with other kinases. Molecular docking studies were done with a library of kinase inhibitors and T95 was found as the potent inhibitor for PknI. Based on structure based pharmacophore analysis of kinase substrate complexes, Lys 41 along with Asp90, Val92 and Asp96 were identified as functionally important residues. Further, we used site directed mutagenesis technique to mutate Lys 41 to Met resulting in defective cell division of Mycobacterium smegmatis mc(2). Overall, the proposed model together with its binding features gained from pharmacophore docking studies helped in identifying ligand inhibitor specific to PknI which was confirmed by laboratory experiments. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining.

    PubMed

    Haidar, Samer; Bouaziz, Zouhair; Marminon, Christelle; Laitinen, Tuomo; Poso, Antti; Le Borgne, Marc; Jose, Joachim

    2017-01-09

    Protein kinase CK2, initially designated as casein kinase 2, is an ubiquitously expressed serine/threonine kinase. This enzyme, implicated in many cellular processes, is highly expressed and active in many tumor cells. A large number of compounds has been developed as inhibitors comprising different backbones. Beside others, structures with an indeno[1,2-b]indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors of human protein kinase CK2, we report here on the generation of common feature pharmacophore model to further explain the binding requirements for human CK2 inhibitors. Nine common chemical features of indeno[1,2-b]indole-type CK2 inhibitors were determined using MOE software (Chemical Computing Group, Montreal, Canada). This pharmacophore model was used for database mining with the aim to identify novel scaffolds for developing new potent and selective CK2 inhibitors. Using this strategy several structures were selected by searching inside the ZINC compound database. One of the selected compounds was bikaverin (6,11-dihydroxy-3,8-dimethoxy-1-methylbenzo[b]xanthene-7,10,12-trione), a natural compound which is produced by several kinds of fungi. This compound was tested on human recombinant CK2 and turned out to be an active inhibitor with an IC50 value of 1.24 µM.

  7. Pharmacophore modeling, homology modeling, and in silico screening reveal mammalian target of rapamycin inhibitory activities for sotalol, glyburide, metipranolol, sulfamethizole, glipizide, and pioglitazone.

    PubMed

    Khanfar, Mohammad A; AbuKhader, Majed M; Alqtaishat, Saja; Taha, Mutasem O

    2013-05-01

    Mammalian target of rapamycin (mTOR) is a serine/threonine kinase and member of the PI3K-related kinase (PIKK) family. It plays a central role in integrating signals from metabolism, energy homeostasis, cell cycle, and stress response. Aberrant PI3K/mTOR activation is commonly observed in diseases such as cancer, diabetes and Alzheimer's disease. Accordingly, we developed common feature binding hypotheses for a set of 6 potent mTOR antagonists. The generated models were validated using receiver operating characteristic (ROC) curve analyses. To gain better insight into ligand-mTOR interactions, a homology model for the kinase domain of mTOR was built using the crystallographic structure of PI3Kγ as template. The optimal pharmacophore model was further improved based on detailed docking studies of potent training compound in the homology model. The modified binding model was employed as 3D search query to screen our in-house-built database of established drugs. Subsequent in vitro screening of captured hits showed that six of them have submicromolar to low micromolar bioactivities, namely, glyburide, metipranolol, sulfamethizole, glipizide, pioglitazone, and sotalol. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. 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.

  9. 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

  10. Search for the Pharmacophore of Histone Deacetylase Inhibitors Using Pharmacophore Query and Docking Study

    PubMed Central

    Haji Agha Bozorgi, Atefeh; Zarghi, Afshin

    2014-01-01

    Histone deacetylase inhibitors have gained a great deal of attention recently for the treatment of cancers and inflammatory diseases. So design of new inhibitors is of great importance in pharmaceutical industries and labs. Creating pharmacophor models in order to design new molecules or search a library for finding lead compounds is of great interest. This approach reduces the overall cost associated with the discovery and development of a new drug. Here we elaborated an exact pharmacophore model for histone deacetylase inhibitors by using pharmacophore query and docking study. The data set used for the modelling exercise comprised of 383 molecules collated from the original literature. These molecules were used to crating the model and docking study was held with Zolinza, the recently FDA approved drug as potent histone deacetylase inhibitor. Our model consists of 5 features: Hydrogen bond donors, Hydrogen bond acceptors, H-bond donor/acceptors, Aromatic ring centers, and hydrophobic centers. With the aid of this pharmacophore model and docking result, 3D searches in large databases can be performed, leading to a significant enrichment of active analogs. PMID:25587304

  11. Design, synthesis and pharmacophoric model building of new 3-alkoxymethyl/3-phenyl indole-2-carboxamides with potential antiproliferative activity.

    PubMed

    Abdelrahman, Mostafa H; Aboraia, Ahmed S; Youssif, Bahaa G M; Elsadek, Bakheet E M

    2016-12-26

    Novel 3-alkoxymethyl/3-phenyl indole-2-carboxamide derivatives were synthesized and evaluated for their anticancer activity. Most of the tested compounds showed moderate to excellent activity against the tested cell lines (MCF7 and HCT116). 3-Phenyl substitution on indole with p-piperidinyl phenethyl 24a and p-dimethylamino phenethyl 24c exhibited anticancer activity against MCF7 with IC50 of 0.13 and 0.14 μm, respectively. Further mechanistic study of the most active compounds through their action on cell cycle showed disturbance in cell cycle progression and cell cycle arrest. For future development of this series of compounds, pharmacophore study was conducted which indicated that the enhancement of the activity could be achieved through the addition of acceptor or donating groups to the already-present indole nucleus.

  12. Hierarchical database screenings for HIV-1 reverse transcriptase using a pharmacophore model, rigid docking, solvation docking, and MM-PB/SA.

    PubMed

    Wang, Junmei; Kang, Xinshan; Kuntz, Irwin D; Kollman, Peter A

    2005-04-07

    In this work, an efficient strategy was presented to search drug leads for human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) using hierarchical database screenings, which included a pharmacophore model, multiple-conformation rigid docking, solvation docking, and molecular mechanics-Poisson-Boltzmann/surface area (MM-PB/SA) sequentially. Encouraging results were achieved in searching a refined available chemical directory (ACD) database: the enrichment factor after the first three filters was estimated to be 25-fold; the hit rate for all the four filters was predicted to be 41% in a control test using 37 known HIV-1 non-nucleoside reverse transcriptase inhibitors; 10 out of 30 promising solvation-docking hits had MM-PB/SA binding free energies better than -6.8 kcal/mol and the best one, HIT15, had -17.0 kcal/mol. In conclusion, the hierarchical multiple-filter database searching strategy is an attractive strategy in drug lead exploration.

  13. 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.

  14. 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

    2014-07-07

    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

  15. 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 Central

    2015-01-01

    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, [125I]-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

  16. Methods and applications of structure based pharmacophores in drug discovery.

    PubMed

    Pirhadi, Somayeh; Shiri, Fereshteh; Ghasemi, Jahan B

    2013-01-01

    A pharmacophore model does not describe a real molecule or a real association of functional groups but illustrates a molecular recognition of a biological target shared by a group of compounds. Pharmacophores also represent the spatial arrangement of essential interactions in a receptor-binding pocket. Structure based pharmacophores (SBPs) can work both with a free (apo) structure or a macromolecule-ligand complex (holo) structure. The SBP methods that derive pharmacophore from protein-ligand complexes use the potential interactions observed between ligand and protein, whereas, the SBP method that aims to derive pharmacophore from ligand free protein, uses only protein active site information. Therefore SBPs do not encounter to challenging problems such as ligand flexibility, molecular alignment as well as proper selection of training set compounds in ligand based pharmacophore modeling. The current review deals with Hot Spot' analysis of binding site to feature generation, several approaches to feature reduction, and considers shape and excluded volumes to SBP model building. This review continues to represent several applications of SBPs in virtual screening especially in parallel screening approach and multi-target drug design. Also it reports the applications of SBPs in QSAR. This review emphasizes that SBPs are valuable tools for hit to lead optimization, virtual screening, scaffold hopping, and multi-target drug design.

  17. 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).

  18. The marine natural-derived inhibitors of glycogen synthase kinase-3β phenylmethylene hydantoins: In vitro and in vivo activities and pharmacophore modeling

    PubMed Central

    Khanfar, Mohammad A.; Asal, Bilal Abu; Mudit, Mudit; Kaddoumi, Amal; El Sayed, Khalid A.

    2009-01-01

    The Red Sea sponge Hemimycale arabica afforded the known (Z)-5-(4-hydroxybenzylidene)-hydantoin (1). This natural phenylmethylene hydantoin (PMH) 1 and the synthetic (Z)-5-(4-(ethylthio)benzylidene)-hydantoin (2) showed potent in vitro and in vivo anti-growth and anti-invasive properties against PC-3M prostate cancer cells in MTT, spheroid disaggregation, and in mice models. To explore a possible molecular target of PMHs, the most potent synthetic analogue 2 has been virtually screened against various protein kinases. Molecular modeling study has shown that 2 can be successfully docked within the binding pocket of glycogen synthase kinase-3beta (GSK-3β) similar to the well-known GSK-3β inhibitor I-5. Several PMHs showed potent in vitro GSK-3β inhibitory activity with an IC50 range of 4–20 µM. The most potent analogue 3 showed a significant increase in liver glycogen level at the 5, 15, and 25 mg/kg dose levels, in vivo. Pharmacophore model was built and validated using in-house database of active and inactive GSK-3β inhibitors. The GSK-3β inhibitory activity of PMHs entitles them to be potential leads for the treatment of cancer, Alzheimer’s disease, bipolar disorders, stroke, different tau pathologies, and type-2 diabetes. PMID:19616957

  19. Antagonists of the human CCR5 receptor as anti-HIV-1 agents. Part 3: a proposed pharmacophore model for 1-[N-(methyl)-N-(phenylsulfonyl)amino]-2-(phenyl)-4-[4-(substituted)piperidin-1-yl]butanes.

    PubMed

    Finke, P E; Meurer, L C; Oates, B; Shah, S K; Loebach, J L; Mills, S G; MacCoss, M; Castonguay, L; Malkowitz, L; Springer, M S; Gould, S L; DeMartino, J A

    2001-09-17

    Structure-activity relationship studies directed toward the optimization of (2S)-2-(3-chlorophenyl)-1-[N-(methyl)-N-(phenylsulfonyl)amino]-4-[4-(substituted)piperidin-1-yl]butanes as CCR5 antagonists resulted in the synthesis of the spiro-indanone derivative 8c (IC50=5 nM). These and previous results are summarized in a proposed pharmacophore model for this class of CCR5 antagonist.

  20. Synthesis, biological evaluation, and three-dimensional in silico pharmacophore model for sigma(1) receptor ligands based on a series of substituted benzo[d]oxazol-2(3H)-one derivatives.

    PubMed

    Zampieri, Daniele; Mamolo, Maria Grazia; Laurini, Erik; Florio, Chiara; Zanette, Caterina; Fermeglia, Maurizio; Posocco, Paola; Paneni, Maria Silvia; Pricl, Sabrina; Vio, Luciano

    2009-09-10

    Novel benzo[d]oxazol-2(3H)-one derivatives were designed and synthesized, and their affinities against sigma receptors were evaluated. On the basis of 31 compounds, a three-dimensional pharmacophore model for the sigma(1) receptor binding site was developed using the Catalyst 4.9 software package. The best 3D pharmacophore hypothesis, consisting of one positive ionizable, one hydrogen bond acceptor, two hydrophobic aromatic, and one hydrophobic features provided a 3D-QSAR model with a correlation coefficient of 0.89. The best hypothesis was also validated by three independent methods, i.e., the Fisher randomization test included in the CatScramble functionality of Catalyst, the leave-one-out test, and activity prediction of an additional test set. The achieved results will allow researchers to use this 3D pharmacophore model for the design and synthesis of a second generation of high affinity sigma(1) ligands, as well as to discover other lead compounds for this class of receptors.

  1. 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

  2. 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

  3. 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

  4. Discovery of novel Bruton's tyrosine kinase inhibitors using a hybrid protocol of virtual screening approaches based on SVM model, pharmacophore and molecular docking.

    PubMed

    Wan, Hua-Lin; Wang, Ze-Rong; Li, Lin-Li; Cheng, Chuan; Ji, Pan; Liu, Jing-Jing; Zhang, Hui; Zou, Jun; Yang, Sheng-Yong

    2012-09-01

    Bruton's tyrosine kinase has emerged as a potential target for the treatment for B-cell malignancies and autoimmune diseases. Discovery of Bruton's tyrosine kinase inhibitors has thus attracted much attention recently. In this investigation, we introduced a hybrid protocol of virtual screening methods including support vector machine model-based virtual screening, pharmacophore model-based virtual screening and docking-based virtual screening for retrieving new Bruton's tyrosine kinase inhibitors from commercially available chemical databases. Performances of the hybrid virtual screening approach were evaluated against a test set, which results showed that the hybrid virtual screening approach significantly shortened the overall screening time, and considerably increased the hit rate and enrichment factor compared with the individual method (SB-VS, PB-VS and DB-VS) or their combinations by twos. This hybrid virtual screening approach was then applied to screen several chemical databases including Specs (202,408 compounds) and Enamine (980,000 compounds) databases. Thirty-nine compounds were selected from the final hits and have been shifted to experimental studies. © 2012 John Wiley & Sons A/S.

  5. Hybrid Receptor-Bound/MM-GBSA-Per-residue Energy-Based Pharmacophore Modelling: Enhanced Approach for Identification of Selective LTA4H Inhibitors as Potential Anti-inflammatory Drugs.

    PubMed

    Appiah-Kubi, Patrick; Soliman, Mahmoud

    2017-03-01

    Leukotriene A4 hydrolase has been identified as an enzyme with dual anti- and pro-inflammatory role, thus, the conversion of leukotriene to leukotriene B4 in the initiation stage of inflammation and the removal of the chemotactic Pro-Gly-Pro tripeptide. These findings make leukotriene A4 hydrolase an attractive drug target: suggesting an innovative approach towards the identification and design of novel class of compounds that can selectively inhibit leukotriene B4 synthesis while sparing the aminopeptidase activity. Previous inhibitors block the dual activity of the enzyme. Recently, a small lead molecule inhibitor denoted as ARM1 has been identified to block the hydrolase activity of leukotriene A4 hydrolase whilst sparing the aminopeptidase activity. In this study, a hybrid receptor-bound/MM-GBSA-per-residue energy based pharmacophore modeling approach was implemented to identify potential selective hydrolase inhibitors of leukotriene A4 hydrolase. In this approach, active site residues that favorably contributed to the binding of the bound conformation of ARM1 were derived from MD ensembles and MM/GBSA thermodynamic calculations. These residues were then mapped to key pharmacophore features of ARM1. The generated pharmacophore model was used to search the ZINC database for 3D structures that match the pharmacophore. Five new compounds have been identified and proposed as potential epoxide hydrolase selective inhibitors of leukotriene A4 hydrolase. Molecular docking and MM/GBSA analyses revealed that, these top five lead-like compounds ZINC00142747, ZINC94260794, ZINC01382396, ZINC02508448, and ZINC53994447 showed better binding affinities to the hydrolase active site pocket compared to ARM1. Per-residue energy decomposition analysis revealed that amino acid residues Phe314, Tyr378, Pro382, Trp311, Val367, and Ala377 are key residues critical in the selective inhibition of these hits. Information highlighted in this study may guide the the design the next

  6. 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.

  7. 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.

  8. 3D QSAR studies, pharmacophore modeling, and virtual screening of diarylpyrazole-benzenesulfonamide derivatives as a template to obtain new inhibitors, using human carbonic anhydrase II as a model protein.

    PubMed

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

    2017-12-01

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

  9. Molecular insight on the binding of NNRTI to K103N mutated HIV-1 RT: molecular dynamics simulations and dynamic pharmacophore analysis.

    PubMed

    Nizami, Bilal; Sydow, Dominique; Wolber, Gerhard; Honarparvar, Bahareh

    2016-10-18

    Regardless of advances in anti-HIV therapy, HIV infection remains an immense challenge due to the rapid onset of mutation instigating drug resistance. Rilpivirine is a second generation di-aryl pyrimidine (DAPY) derivative, known to effectively inhibit wild-type (WT) as well as various mutant HIV-1 reverse transcriptase (RT). In this study, a cumulative 240 ns of molecular dynamic (MD) simulations of WT HIV-1 RT and its corresponding K103N mutated form, complexed with rilpivirine, were performed in solution. Conformational analysis of the NNRTI inside the binding pocket (NNIBP) revealed the ability of rilpivirine to adopt different conformations, which is possibly the reason for its reasonable activity against mutant HIV-1 RT. Binding free energy (MM-PB/GB SA) calculations of rilpivirine with mutant HIV-1 RT are in agreement with experimental data. The dynamics of interaction patterns were investigated based on the MD simulations using dynophores, a novel approach for MD-based ligand-target interaction mapping. The results from this interaction profile analysis suggest an alternate interaction between the linker N atom of rilpivirine and Lys 101, potentially providing the stability for ligand binding. PCA analysis and per residue fluctuation has highlighted the significant role of flexible thumb and finger sub-domains of RT in its biological activity. This study investigated the underlying reason for rilpivirine's improved inhibitory profile against mutant RT, which could be helpful to understand the molecular basis of HIV-1 RT drug resistance and design novel NNRTIs with improved drug resistance tolerance.

  10. 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.

  11. 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

  12. 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.

  13. Identification of a new class of potent Cdc7 inhibitors designed by putative pharmacophore model: Synthesis and biological evaluation of 2,3-dihydrothieno[3,2-d]pyrimidin-4(1H)-ones.

    PubMed

    Kurasawa, Osamu; Oguro, Yuya; Miyazaki, Tohru; Homma, Misaki; Mori, Kouji; Iwai, Kenichi; Hara, Hideto; Skene, Robert; Hoffman, Isaac; Ohashi, Akihiro; Yoshida, Sei; Ishikawa, Tomoyasu; Cho, Nobuo

    2017-04-01

    Cell division cycle 7 (Cdc7) is a serine/threonine kinase that plays important roles in the regulation of DNA replication process. A genetic study indicates that Cdc7 inhibition can induce selective tumor-cell death in a p53-dependent manner, suggesting that Cdc7 is an attractive target for the treatment of cancers. In order to identify a new class of potent Cdc7 inhibitors, we generated a putative pharmacophore model based on in silico docking analysis of a known inhibitor with Cdc7 homology model. The pharmacophore model provided a minimum structural motif of Cdc7 inhibitor, by which preliminary medicinal chemistry efforts identified a dihydrothieno[3,2-d]-pyrimidin-4(1H)-one scaffold having a heteroaromatic hinge-binding moiety. The structure-activity relationship (SAR) studies resulted in the discovery of new, potent, and selective Cdc7 inhibitors 14a, c, e. Furthermore, the high selectivity of 14c, e for Cdc7 over Rho-associated protein kinase 1 (ROCK1) is discussed by utilizing a docking study with Cdc7 and ROCK2 crystal structures.

  14. 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

  15. In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors.

    PubMed

    Mahapatra, Manoj Kumar; Bera, Krishnendu; Singh, Durg Vijay; Kumar, Rajnish; Kumar, Manoj

    2017-04-21

    Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.

  16. Toll-Like Receptor 7 Agonists: Chemical Feature Based Pharmacophore Identification and Molecular Docking Studies

    PubMed Central

    Sun, Lidan; Zhang, Liangren; Sun, Gang; Wang, Zhanli; Yu, Yongchun

    2013-01-01

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

  17. Three-dimensional pharmacophore screening for fentanyl derivatives☆

    PubMed Central

    Liu, Ming; Sun, Zhiguo; Hu, Wenxiang

    2012-01-01

    Fentanyl is a highly selective μ-opioid receptor agonist with high analgesic activity. Three-dimensional pharmacophore models were built from a set of 50 fentanyl derivatives. These were employed to elucidate ligand-receptor interactions using information derived only from the ligand structure to identify new potential lead compounds. The present studies demonstrated that three hydrophobic regions, one positive ionizable region and two hydrogen bond acceptor region sites located on the molecule seem to be essential for analgesic activity. The results of the comparative molecular field analysis model suggested that both steric and electrostatic interactions play important roles. The contributions from steric and electrostatic fields for the model were 0.621 and 0.379, respectively. The pharmacophore model provides crucial information about how well the common features of a subject molecule overlap with the hypothesis model, which is very valuable for designing and optimizing new active structures. PMID:25657673

  18. 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

  19. Pharmacophore development for antagonists at α1 adrenergic receptor subtypes

    NASA Astrophysics Data System (ADS)

    Bremner, J. B.; Coban, B.; Griffith, R.

    1996-12-01

    Many receptors, including α1 adrenergic receptors, have a range of subtypes. This offers possibilities for the development of highly selective antagonists with potentially fewer detrimental effects. Antagonists developed for α1A receptors, for example, would have potential in the treatment of benign prostatic hyperplasia. As part of the molecular design process, structural features necessary for the selective affinity for α1A and α1B adrenergic receptors have been investigated. The molecular modelling software (particularly the Apex module) of Molecular Simulations, Inc. was used to develop pharmacophore models for these two subtypes. Low-energy conformations of a set of known antagonists were used as input, together with a classification of the receptor affinity data. The biophores proposed by the program were evaluated and pharmacophores were proposed. The pharmacophore models were validated by testing the fit of known antagonists, not included in the training set. The critical structural feature for selectivity between the α1A and α1B adrenergic receptor sites is the distance between the basic nitrogen atom and the centre of an aromatic ring system. This will be exploited in the design and synthesis of structurally new selective antagonists for these sites.

  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. 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

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

    PubMed

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

    2008-05-01

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

  3. Pd-catalyzed direct C-H bond functionalization of spirocyclic σ1 ligands: generation of a pharmacophore model and analysis of the reverse binding mode by docking into a 3D homology model of the σ1 receptor.

    PubMed

    Meyer, Christina; Schepmann, Dirk; Yanagisawa, Shuichi; Yamaguchi, Junichiro; Dal Col, Valentina; Laurini, Erik; Itami, Kenichiro; Pricl, Sabrina; Wünsch, Bernhard

    2012-09-27

    To explore the hydrophobic binding region of the σ(1) receptor protein, regioisomeric spirocyclic thiophenes 9-11 were developed as versatile building blocks. Regioselective α- and β-arylation using the catalyst systems PdCl(2)/bipy/Ag(2)CO(3) and PdCl(2)/P[OCH(CF(3))(2)](3)/Ag(2)CO(3) allowed the introduction of various aryl moieties at different positions in the last step of the synthesis. The increasing σ(1) affinity in the order 4 < 5/6 < 7/8 indicates that the positions of the additional aryl moiety and the S atom in the spirocyclic thiophene systems control the σ(1) affinity. The main features of the pharmacophore model developed for this class of σ(1) ligands are a positive ionizable group, a H-bond acceptor group, two hydrophobic moieties, and one hydrophobic aromatic group. Docking of the ligands into a σ(1) 3D homology model via molecular mechanics/Poisson-Boltzmann surface area calculations led to a very good correlation between the experimentally determined and estimated free energy of receptor binding. These calculations support the hypothesis of a reverse binding mode of ligands bearing the aryl moiety at the "top" (compounds 2, 3, 7, and 8) and "left" (compounds 4, 5, and 6) positions, respectively.

  4. Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

    NASA Astrophysics Data System (ADS)

    Fayaz, S. M.; Rajanikant, G. K.

    2014-07-01

    Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

  5. Stepwise development of structure-activity relationship of diverse PARP-1 inhibitors through comparative and validated in silico modeling techniques and molecular dynamics simulation.

    PubMed

    Halder, Amit K; Saha, Achintya; Saha, Krishna Das; Jha, Tarun

    2015-01-01

    Inhibitors of poly (ADP-ribose) polymerase-1 (PARP-1) enzyme are useful for the treatment of various diseases including cancer. Comparative in silico studies were performed on different ligand-based (2D-QSAR, Kernel-based partial least square (KPLS) analysis, Pharmacophore Search Engine (PHASE) pharmacophore mapping), and structure-based (molecular docking, MM-GBSA analyses, Gaussian-based 3D-QSAR analyses on docked poses) modeling techniques to explore the structure-activity relationship of a diverse set of PARP-1 inhibitors. Two-dimensional (2D)-QSAR highlighted the importance of charge topological index (JGI7), fractional polar surface area (JursFPSA3), and connectivity index (CIC2) along with different molecular fragments. Favorable and unfavorable fingerprints were demonstrated in KPLS analysis, whereas important pharmacophore features (one acceptor, one donor, and two ring aromatic) along with favorable and unfavorable field effects were demonstrated in PHASE-based pharmacophore model. MM-GBSA analyses revealed significance of different polar, non-polar, and solvation energies. Docking-based alignment of ligands was used to perform Gaussian-based 3D-QSAR study that further demonstrated importance of different field effects. Overall, it was found that polar interactions (hydrogen bonding, bridged hydrogen bonding, and pi-cation) play major roles for higher activity. Steric groups increase the total contact surface area but it should have higher fractional polar surface area to adjust solvation energy. Structure-based pharmacophore mapping spotted the positive ionizable feature of ligands as the most important feature for discriminating highly active compounds from inactives. Molecular dynamics simulation, conducted on highly active ligands, described the dynamic behaviors of the protein complexes and supported the interpretations obtained from other modeling analyses. The current study may be useful for designing PARP-1 inhibitors.

  6. Equivalent Dynamic Models.

    PubMed

    Molenaar, Peter C M

    2017-02-16

    Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

  7. Substructural QSAR approaches and topological pharmacophores.

    PubMed Central

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

    1985-01-01

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

  8. A Novel Approach for the Identification of Pharmacophores Through Differential Toxicity Analysis of Estrogen Receptor Positive and Negative Cell Lines

    DTIC Science & Technology

    2008-07-31

    Professor of Pharmacology and Toxicology at the University of Louisville’s James Graham Brown Cancer Center, along with significant startup package...appropriate size for developing pharmacophores for later 3-D QSAR modeling. Moreover, from a practical point, models of atom size 12 had roughly nearly...association of fragments (pharmacophores) to chemicals for QSAR analyses. For the MCF-7 - MDA-MB-231 models we selected compounds NSC 625587

  9. 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.

  10. Novel approach for efficient pharmacophore-based virtual screening: method and applications.

    PubMed

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

    2009-10-01

    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 data set of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) data set 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.

  11. Thermal dynamic modeling study

    NASA Technical Reports Server (NTRS)

    Ojalvo, I. U.

    1972-01-01

    Some thermal dynamic requirements associated with the space shuttle vehicle are reviewed. Pertinent scaling laws are discussed and recommendations are offered regarding the need for conducting reduced-scale dynamic tests of major components at elevated temperatures. Items considered are the development and interpretation of thermal dynamic structural scaling laws, the identification of major related problem areas and a presentation of viable model fabrication, instrumentation, and test procedures.

  12. Novel method for pharmacophore analysis by examining the joint pharmacophore space.

    PubMed

    Ranu, Sayan; Singh, Ambuj K

    2011-05-23

    We propose a novel method for pharmacophore analysis by examining the Joint Pharmacophore Space of chemical compounds, targets, and chemical/biological properties. The proposed approach is a notable deviation from existing techniques that analyze compounds on a target-by-target basis, aimed at extracting and optimizing a specific pharmacophore. The underlying geometry of the pharmacophores is responsible for binding between compounds and targets as well as properties of compounds such as Blood Brain Barrier permeability. The identification of this joint space enables us to cluster and classify similar pharmacophores based on geometric arrangements, analyze the diversity of this space, ascribe positive/negative properties to the subspaces, and query and mine a database of compounds for presence or absence of activity. Extensive experiments are carried out to validate the presence of subspaces that uniquely identify geometric configurations conforming to certain biological activities. The discriminative potential of these subspaces is also verified by employing them as a molecular descriptor. Empirical results show promising performance in terms of classification quality highlighting the utility of mining the joint pharmacophore space.

  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. 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…

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

    PubMed

    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 for example, 41 and 42, was exhibited in a stereochemical preference similar to pyran TUI for example, D-161. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. 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

  17. Dynamic model for biospeckle.

    PubMed

    Paixão, Crysttian Arantes; da Costa, Antonio Tavares

    2013-06-01

    This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.

  18. Identification of non-resistant ROS-1 inhibitors using structure based pharmacophore analysis.

    PubMed

    Pathak, Disha; Chadha, Navriti; Silakari, Om

    2016-11-01

    Proto-oncogene receptor tyrosine kinase ROS-1 plays a key role in regulating a variety of cancers mainly non-small cell lung cancer (NSCLC). The marketed ROS-1 inhibitors such as Crizotinib suffer from the tribulations of growing resistance due to mutations primarily Gly2032Arg in the ROS-1 protein. To curb the problem of resistance, researchers have developed inhibitors such as Lorlatinib against the mutant protein. The present study was designed to identify inhibitors against wild type (WT) as well as mutant ROS-1 protein that will offer a broader spectrum of activity. Exploring crystal structure of ROS-1 complexed with Lorlatinib, receptor-ligand pharmacophore model was developed using Discovery Studio (DS) software. The developed pharmacophore model consisted of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) and two hydrophobic features (HY), subsequently utilized for virtual screening of commercially available databases and the retrieved hits were further subjected to fitness score and Lipinski's filter. Thereafter, the retrieved hits were docked in WT and mutated (Gly2032Arg) proteins of ROS-1. Total five molecules were retrieved with good docking scores and good binding interactions within the active site of WT and mutated ROS-1. The binding energies of the ligand-receptor complexes were predicted via calculation of MM-GBSA score. To predict the stability of the ligand receptor complexes with mutant and wild type proteins, molecular dynamic simulation was performed. Thus, these identified hits show good binding affinities with WT and mutant ROS-1 proteins that may be further evaluated for their in-vitro/in-vivo activity.

  19. Pharmacophore-driven identification of PPARγ agonists from natural sources

    NASA Astrophysics Data System (ADS)

    Petersen, Rasmus K.; Christensen, Kathrine B.; Assimopoulou, Andreana N.; Fretté, Xavier; Papageorgiou, Vassilios P.; Kristiansen, Karsten; Kouskoumvekaki, Irene

    2011-02-01

    In a search for more effective and safe anti-diabetic compounds, we developed a pharmacophore model based on partial agonists of PPARγ. The model was used for the virtual screening of the Chinese Natural Product Database (CNPD), a library of plant-derived natural products primarily used in folk medicine. From the resulting hits, we selected methyl oleanonate, a compound found, among others, in Pistacia lentiscus var. Chia oleoresin (Chios mastic gum). The acid of methyl oleanonate, oleanonic acid, was identified as a PPARγ agonist through bioassay-guided chromatographic fractionations of Chios mastic gum fractions, whereas some other sub-fractions exhibited also biological activity towards PPARγ. The results from the present work are two-fold: on the one hand we demonstrate that the pharmacophore model we developed is able to select novel ligand scaffolds that act as PPARγ agonists; while at the same time it manifests that natural products are highly relevant for use in virtual screening-based drug discovery.

  20. Dynamic causal modelling revisited.

    PubMed

    Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter

    2017-02-17

    This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries.

  1. 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.

  2. Identification of Novel HIV 1- Protease Inhibitors: Application of Ligand and Structure Based Pharmacophore Mapping and Virtual Screening

    PubMed Central

    Yadav, Divya; Paliwal, Sarvesh; Yadav, Rakesh; Pal, Mahima; Pandey, Anubhuti

    2012-01-01

    A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities. PMID:23145032

  3. Corruption dynamics model

    NASA Astrophysics Data System (ADS)

    Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

    2017-07-01

    The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

  4. Pharmacophore identification and validation study of CK2 inhibitors using CoMFA/CoMSIA.

    PubMed

    Morshed, Mohammad Neaz; Muddassar, Muhammad; Pasha, Farhan Ahmad; Cho, Seung Joo

    2009-08-01

    Protein kinase CK2, also known as casein kinase-2, has been found to be involved in cell growth, proliferation and suppression of apoptosis, which is related to human cancers. The series of compounds were identified as casein kinase-2 inhibitors and their inhibitory activities are a function of a variation of their structures. The current study deals with the pharmacophore identification and, accordingly, the three-dimensional quantitative structure-activity relationship model development using Pharmacophore Alignment and Scoring Engine. Several hypotheses were developed for the molecular alignments. On the basis of statistical values, the best-fitted model was identified and the same alignment was used for 3D-QSAR using comparative molecular field analysis/comparative molecular similarity index analysis. Both the CoMFA (R(2)(CV) = 0.58, R(2) = 0.82 and r(2)(pred) = 0.62) and the comparative molecular similarity index analysis (R(2)(CV) = 0.74, R(2) = 0.98 and r(2)(pred) = 0.81) gave reasonable results. Besides pharmacophore-based alignment, the maximum common substructure-based alignment was also used for the comparative molecular field analysis and comparative molecular similarity index analysis. The pharmacophore-based alignment was more prominent and it has provided important information for the modelling of potent inhibitors. The overall study implies that a highly positive and bulky group with H-bond donating property is desirable around the nitrogen atom adjacent to the pyrrolidine ring.

  5. Pharmacophore and Virtual Screening of JAK3 inhibitors.

    PubMed

    Rajeswari, Murugesan; Santhi, Natchimuthu; Bhuvaneswari, Vembu

    2014-01-01

    Janus kinase 3 (JAK3) is a non-receptor tyrosine kinases family of protein which is comprised of JAK1, JAK2, JAK3 and TYK2. It plays an important role in immune function and lymphoid development and it only resides in the hematopoietic system. Therefore, selective targeting JAK3 is a rational approach in developing new therapeutic molecule. In this study, about 116 JAK3 inhibitors were collected from the literature and were used to build four-point pharmacophore model using Phase (Schrodinger module). The statistically significant pharmacophore hypothesis of AAHR.92 with r2 value of 0.942 was used as 3D query to search against 3D database namely Zincpharmer. A total of 2, 27,483 compounds obtained as hit were subjected to high throughput virtual screening (HTVS module of Schrodinger). Among the hits, ten compounds with good G-score ranging from -12.96 to -11.18 with good binding energy to JAK3 were identified.

  6. Modelling sea ice dynamics

    NASA Astrophysics Data System (ADS)

    Murawski, Jens; Kleine, Eckhard

    2017-04-01

    Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.

  7. 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.

  8. Modeling Fractal Dynamics

    NASA Astrophysics Data System (ADS)

    West, Bruce J.

    The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.

  9. 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.

  10. [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.

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

    PubMed Central

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

    2008-01-01

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

  12. 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.

  13. Revisiting de novo drug design: receptor based pharmacophore screening.

    PubMed

    Amaravadhi, Harikishore; Baek, Kwanghee; Yoon, Ho Sup

    2014-01-01

    De novo drug design methods such as receptor or protein based pharmacophore modeling present a unique opportunity to generate novel ligands by employing the potential binding sites even when no explicit ligand information is known for a particular target. Recent developments in molecular modeling programs have enhanced the ability of early programs such as LUDI or Pocket that not only identify the key interactions or hot spots at the suspected binding site, but also and convert these hot spots into three-dimensional search queries and virtual screening of the property filtered synthetic libraries. Together with molecular docking studies and consensus scoring schemes they would enrich the lead identification processes. In this review, we discuss the ligand and receptor based de novo drug design approaches with selected examples.

  14. Comparative molecular field analysis to derive pharmacophore maps for disposition parameters of intravenous anaesthetic agents.

    PubMed

    Sear, J W

    2012-10-01

    The present study examines the molecular basis of the disposition kinetics for i.v. hypnotic agents using comparative molecular field analysis (CoMFA). The systemic clearance (Cl(s) litre min(-1)) and apparent volume of distribution at steady state (Vd(ss) litres) for 14 i.v. anaesthetics in human subjects were obtained from the literature, or from unpublished data, and used to form CoMFA models for the two aspects of drug disposition. Molecular alignment was achieved by field-fit minimization with the lead structure for all models eltanolone. The resulting pharmacophore maps were also compared with the pharmacophores for cardiovascular depression (expressed in terms of the drug concentration in 50% patients, associated with a 20% decrease in mean arterial pressure during infusion anaesthesia in the absence of other adjuvant drugs or noxious stimulation), which were taken from the literature. The CoMFA model for Cl was based on two latent variables, explained 95.2% of the variance in observed activities, and showed good intrinsic predictability (cross-validated q(2) 0.663). The model for Vd(ss) was also based on two latent variables: r(2) 0.986 and q(2) 0.718. Comparison of the pharmacophores for the two disposition parameters showed poor correlation for both electrostatic and steric regions (r=-0.220 and 0.018; both NS). The relative contributions of electrostatic and steric interactions differed between the models (Cl(s) 1.9:1; Vd(ss) 2.5:1). Comparison with the cardiovascular pharmacophores depression models gave r values of 0.551 (P<0.05) and 0.407 (ns) for Cl(s) (for electrostatic and steric models) and -0.225 and -0.448 for Vd(ss) (both ns). Comparison of CoMFA models for drug disposition show only small elements of commonality, suggesting different molecular features may be responsible are two properties. There was better similarity for both disposition pharmacophores with the pharmacophores for cardiovascular depression.

  15. Relativistic dynamical collapse model

    NASA Astrophysics Data System (ADS)

    Pearle, Philip

    2015-05-01

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

  16. 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

  17. Pharmacophore based 3DQSAR of phenothiazines as specific human butyrylcholinesterase inhibitors for treatment of Alzheimer's disease.

    PubMed

    Kundaikar, Harish S; Agre, Neha P; Degani, Mariam S

    2014-01-01

    Quantitative three dimensional structure activity relationship (3D-QSAR) studies were performed on phenothiazine derivatives as Butyrylcholinesterase (BuChE) inhibitors. Pharmacophore Alignment and Scoring Engine (PHASE) was used to develop predictive Common Pharmacophore Hypotheses (CPHs). The alignment thus obtained was used for Comparative Molecular Field Analysis (CoMFA)/Comparative Molecular Similarity Indices Analysis (CoMSIA) model development. A fourpoint common pharmacophore hypothesis, comprising of one acceptor, one hydrophobic region and two aromatic ring centres was generated. A structurally diverse set of 80 molecules was used of which 56 were grouped into training set to develop the model and the rest 24 molecules into test set to validate the CoMFA/CoMSIA models. The models so developed showed a good r(2)predictive of 0.7587 for CoMFA and 0.7737 for CoMSIA. CoMFA and CoMSIA models had excellent Q(2) (cross-validated coefficient) of 0.7125 and 0.7093, respectively which showed high correlative and predictive abilities of the models. The 3-D contour maps of CoMFA/CoMSIA provided interpretable explanation of SAR for the compounds and also permitted interesting conclusions about the substituent effects on the phenothiazine derivatives. The outcomes of the study would help in the rational design of novel and potent therapeutic agents as specific BuChE inhibitors for symptomatic or disease modifying treatment of AD.

  18. 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.

  19. Identification of potential ACAT-2 selective inhibitors using pharmacophore, SVM and SVR from Chinese herbs.

    PubMed

    Qiao, Lian-Sheng; Zhang, Xian-Bao; Jiang, Lu-di; Zhang, Yan-Ling; Li, Gong-Yu

    2016-11-01

    Acyl-coenzyme A cholesterol acyltransferase (ACAT) plays an important role in maintaining cellular and organismal cholesterol homeostasis. Two types of ACAT isozymes with different functions exist in mammals, named ACAT-1 and ACAT-2. Numerous studies showed that ACAT-2 selective inhibitors are effective for the treatment of hypercholesterolemia and atherosclerosis. However, as a typical endoplasmic reticulum protein, ACAT-2 protein has not been purified and revealed, so combinatorial ligand-based methods might be the optimal strategy for discovering the ACAT-2 selective inhibitors. In this study, selective pharmacophore models of ACAT-1 inhibitors and ACAT-2 inhibitors were built, respectively. The optimal pharmacophore model for each subtype was identified and utilized as queries for the Traditional Chinese Medicine Database screening. A total of 180 potential ACAT-2 selective inhibitors were obtained, which were identified using an ACAT-2 pharmacophore and not by our ACAT-1 model. Selective SVM model and bioactive SVR model were generated for further identification of the obtained ACAT-2 inhibitors. Ten compounds were finally obtained with predicted inhibitory activities toward ACAT-2. Hydrogen bond acceptor, 2D autocorrelations, GETAWAY descriptors, and BCUT descriptors were identified as key structural features for selectivity and activity of ACAT-2 inhibitors. This study provides a reasonable ligand-based approach to discover potential ACAT-2 selective inhibitors from Chinese herbs, which could help in further screening and development of ACAT-2 selective inhibitors.

  20. The active analog approach applied to the pharmacophore identification of benzodiazepine receptor ligands

    NASA Astrophysics Data System (ADS)

    Tebib, Souhail; Bourguignon, Jean-Jacques; Wermuth, Camille-Georges

    1987-07-01

    Applied to seven potent benzodiazepine-receptor ligands belonging to chemically different classes, the active analog approach allowed the stepwise identification of the pharmacophoric pattern associated with the recognition by the benzodiazepine receptor. A unique pharmacophore model was derived which involves six critical zones: (a) a π-electron rich aromatic (PAR) zone; (b) two electron-rich zones δ1 and δ2 placed at 5.0 and 4.5 Å respectively from the reference centroid in the PAR zone; (c) a freely rotating aromatic ring (FRA) region; (d) an out-of-plane region (OPR), strongly associated with agonist properties; and (e) an additional hydrophobic region (AHR). The model accommodates all presently known ligands of the benzodiazepine receptor, identifies sensitivity to steric hindrance close to the δ1 zone, accounts for R and S differential affinities and distinguishes requirements for agonist versus non-agonist activity profiles.

  1. Structural functions of the sweet pharmacophore.

    PubMed

    Birch, G G; Dziedzic, S Z; Shallenberger, R S; Lindley, M G

    1981-03-01

    The relative sweetness, onset times, and durations of response of D-glucose, D-xylose, D-quinovose, D-galactose, L-arabinose, and D-fucose were determined at four temperatures. The results can be interpreted by simple concepts of intramolecular hydrogen bonding which indicate that the so-called gamma-function of the tripartite AH,B, gamma sweet pharmacophore plays little or no part in sugar sweetness. Probably the Lemieux effect (intramolecular hydrogen bonding between the hydroxymethyl substituent and the 4-hydroxy group) is of overriding importance in determining sugar sweetness, and the separate features of intensity and time of response indicate distinct functions of chemoreception. The absence of a gamma-function in simple hydrophilic molecules such as glucose has already been emphasized. This function distinguishes them from the artificial sweetners such as saccharin, which may be 500 times or more sweeter than sucrose, depending on their stereostructure and lipophilicity.

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

    PubMed

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

    2005-01-01

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

  3. 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.

  4. 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

  5. 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.

  6. The μ-and δ-opioid pharmacophore conformations of cyclic β-casomorphin analogues indicate docking of the Phe3 residue to different domains of the opioid receptors

    NASA Astrophysics Data System (ADS)

    Brandt, Wolfgang; Stoldt, Matthias; Schinke, Heiko

    1996-06-01

    Cyclic β-casomorphin analogues with a d-configured amino acid residue in position 2, such as Tyr-c[-Xaa-Phe-Pro-Gly-] and Tyr-c[-Xaa-Phe- d-Pro-Gly-] (Xaa= d-A2bu, d-Orn, d-Lys) were found to bind to the μ-opioid receptor as well as to the δ-opioid receptor, whereas the corresponding l-Xaa2 derivatives are nearly inactive at both. Low-energy conformers of both active and nearly inactive derivatives have been determined in a systematic conformational search or by molecular dynamics simulations using the TRIPOS force field. The obatained conformations were compared with regard to a model for μ-selective opiates developed by Brandt et al. [Drug Des. Discov., 10 (1993) 257]. Superpositions as well as electrostatic, lipophilic and hydrogen bonding similarities with the δ-opioid receptor pharmacophore conformation of t-Hpp-JOM-13 proposed by Mosberg et al. [J. Med. Chem., 37 (1994) 4371, 4384] were used to establish the probable δ-pharmacophoric cyclic β-casomorphin conformations. These conformations were also compared with a δ-opioid agonist (SNC 80) and the highly potent antagonist naltrindole. These investigations led to a prediction of the μ-and δ-pharmacophore structures for the cyclic β-casomorphins. Interestingly, for the inactive compounds such conformations could not be detected. The comparison between the μ-and δ-pharmacophore conformations of the cyclic β-casomorphins demonstrates not only differences in spatial orientation of both aromatic groups, but also in the backbone conformations of the ring part. In particular, the differences in Φ2 and Ψ2 (μ≈70°,-80°; δ≈165°,55°) cause a completely different spatial arrangement of the cyclized peptide rings when all compounds are matched with regard to maximal spatial overlap of the tyrosine residue. Assuming that both the μ-and δ-pharmacophore conformations bind with the tyrosine residue in a similar orientation at the same transmembrane domain X of their receptors, the side chain of Phe3

  7. Discovery of multitarget inhibitors by combining molecular docking with common pharmacophore matching.

    PubMed

    Wei, Dengguo; Jiang, Xiaolu; Zhou, Lu; Chen, Jing; Chen, Zheng; He, Chong; Yang, Kun; Liu, Ying; Pei, Jianfeng; Lai, Luhua

    2008-12-25

    Multitarget drugs have been to be found effective in controlling complex diseases. However, how to design multitarget drugs presents a great challenge. We have developed a computer-assisted strategy to screen for multitarget inhibitors using a combination of molecular docking and common pharmacophore matching. This strategy was successfully applied to screen for dual-target inhibitors against both the human leukotriene A(4) hydrolase (LTA4H-h) and the human nonpancreatic secretory phospholipase A2 (hnps-PLA2). Three compounds screened from the chemical database MDL Available Chemical Directory were found to inhibit these two enzymes at the 10 microM level. Moreover, one synthetic compound matching the common pharmacophores inhibits LTA4H-h and hnps-PLA2 with IC(50) values of 35 nM and 7.3 microM, respectively. The common pharmacophore model can also be used to search small molecule databases or collections of existing inhibitors, as well as to guide combinatorial library design to search for ideal multitarget inhibitors.

  8. Multiple spatially related pharmacophores define small molecule inhibitors of OLIG2 in glioblastoma

    PubMed Central

    Chao, Ying; Babic, Ivan; Nurmemmedov, Elmar; Pastorino, Sandra; Jiang, Pengfei; Calligaris, David; Agar, Nathalie; Scadeng, Miriam; Pingle, Sandeep C.; Wrasidlo, Wolfgang; Makale, Milan T.; Kesari, Santosh

    2017-01-01

    Transcription factors (TFs) are a major class of protein signaling molecules that play key cellular roles in cancers such as the highly lethal brain cancer—glioblastoma (GBM). However, the development of specific TF inhibitors has proved difficult owing to expansive protein-protein interfaces and the absence of hydrophobic pockets. We uniquely defined the dimerization surface as an expansive parental pharmacophore comprised of several regional daughter pharmacophores. We targeted the OLIG2 TF which is essential for GBM survival and growth, we hypothesized that small molecules able to fit each subpharmacophore would inhibit OLIG2 activation. The most active compound was OLIG2 selective, it entered the brain, and it exhibited potent anti-GBM activity in cell-based assays and in pre-clinical mouse orthotopic models. These data suggest that (1) our multiple pharmacophore approach warrants further investigation, and (2) our most potent compounds merit detailed pharmacodynamic, biophysical, and mechanistic characterization for potential preclinical development as GBM therapeutics. PMID:26517684

  9. 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

  10. Generative models of conformational dynamics.

    PubMed

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term 'generative' refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GRAPHICAL MODELS OF ENERGY LANDSCAPES), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc.) from long timescale simulation data.

  11. 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.

  12. Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity.

    PubMed

    Vyas, V K; Qureshi, G; Ghate, M; Patel, H; Dalai, S

    2016-06-01

    Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC50 values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere-Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a QFIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.

  13. Combined pharmacophore and 3D-QSAR study on a series of Staphylococcus aureus Sortase A inhibitors.

    PubMed

    Uddin, Reaz; Lodhi, Mazhar U; Ul-Haq, Zaheer

    2012-08-01

    Methicillin resistant Staphylococcus aureus has become a major health concern and it requires new therapeutic agents. Staphylococcus aureus Sortase A enzyme contributes in adherence of bacteria with the cell wall of host cell; consequently, inhibition of S. aureus Sortase A by small molecules could be employed as potential antibacterial agents against methicillin resistant S. aureus. Current study focused on the identification of 3D pharmacophoric features within a series of rhodanine, pyridazinone, and pyrazolethione analogs as S. aureus Sortase A inhibitors. Pharmacophore model was constructed employing representative molecules using Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database. The identified pharmacophoric points were then utilized to create alignment hypothesis for three-dimensional quantitative structure-activity relationships. Outcome of comparative molecular field analysis and comparative molecular similarity indices analysis experiments were in good agreement (comparative molecular field analysis: q(2) = 0.562 and r(2) = 0.995, comparative molecular similarity indices analysis: q(2) = 0.549 and r(2) = 0.978) and capable of explaining the variance in biological activities coherently with respect to the structural features of compounds. The results were also found in concurrence with the outcome of pharmacophoric features.

  14. Predictive models of forest dynamics.

    PubMed

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

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

    PubMed

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

    2015-06-01

    Flupyradifurone (4-[(2,2-difluoroethyl)amino]-2(5H)-furanone), a member of the new class of butenolide insecticides, contains a novel bioactive scaffold as pharmacophore. It is very versatile in terms of application methods to a variety of crops, exhibits excellent and fast action against a broad spectrum of sucking pest insects including selected neonicotinoid resistant pest populations such as whiteflies and aphids expressing metabolic resistance mechanisms. As a partial agonist flupyradifurone reversibly binds to insect nicotinic acetylcholine receptors (nAChRs) and lacks metabolization by CYP6CM1, a cytochrome P450 over-expressed in cotton whiteflies resistant to imidacloprid and pymetrozine. The butenolide insecticides exhibit structure-activity relationships (SAR) that are different from other nAChR agonists such as the classes of neonicotinoids and sulfoximines. The paper briefly reviews the discovery of the butenolide insecticide flupyradifurone, its SAR differentiating it from established nAChR agonists and a molecular docking approach using the binding site model of CYP6CM1vQ of Bemisia tabaci known to confer metabolic resistance to neonicotinoid insecticides. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Pharmacophore guided discovery of small-molecule interleukin 15 inhibitors.

    PubMed

    Żyżyńska-Granica, Barbara; Trzaskowski, Bartosz; Niewieczerzał, Szymon; Filipek, Sławomir; Zegrocka-Stendel, Oliwia; Dutkiewicz, Małgorzata; Krzeczyński, Piotr; Kowalewska, Magdalena; Koziak, Katarzyna

    2017-08-18

    Upregulation of interleukin 15 (IL-15) contributes directly i.a. to the development of inflammatory and autoimmune diseases. Selective blockade of IL-15 aimed to treat rheumatoid arthritis, psoriasis and other IL-15-related disorders has been recognized as an efficient therapeutic method. The aim of the study was to identify small molecules which would interact with IL-15 or its receptor IL-15Rα and inhibit the cytokine's activity. Based on the crystal structure of IL-15Rα·IL-15, we created pharmacophore models to screen the ZINC database of chemical compounds for potential IL-15 and IL-15Rα inhibitors. Twenty compounds with the highest predicted binding affinities were subjected to in vitro analysis using human peripheral blood mononuclear cells to validate in silico data. Twelve molecules efficiently reduced IL-15-dependent TNF-α and IL-17 synthesis. Among these, cefazolin - a safe first-generation cephalosporin antibiotic - holds the highest promise for IL-15-directed therapeutic applications. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  1. 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.

  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. 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)

  4. Mining the Chemical Abstracts database with pharmacophore-based queries.

    PubMed

    Bremner, John B; Castle, Kao; Griffith, Renate; Keller, Paul A; Ridley, Damon D

    2002-12-01

    A method is described to convert 3D patterns of pharmacophoric groups into 2D queries for molecular substructure searches of the Chemical Abstracts database with SciFinder Scholar. The results of such searches and the options for refinement of the hit lists are presented using a rigid tetrahydroisoquinoline-carbazole (IQC) hybrid molecule fitted onto previously developed pharmacophores for subtype-selective alpha1-adrenergic receptor antagonists as an example. The compounds retrieved were further analysed by limiting their physical properties to 'drug-like' ranges and by enumerating the ring skeletons they contain. Selected ring skeletons were evaluated by fitting them on to the original pharmacophores. Several structurally novel rigid ring skeletons were found with this new database mining technique which are potentially useful as leads in the design of alpha1B selective adrenergic receptor antagonists.

  5. Qualitative and quantitative pharmacophore-similarity assessment of anthranilamide-based factor Xa inhibitors: applications on similar molecules with identical biological endpoints.

    PubMed

    Kumar, Sivakumar Prasanth; Rawal, Rakesh M; Pandya, Himanshu A; Jasrai, Yogesh T

    2016-01-01

    It is a conventional practice to exclude molecules with identical biological endpoints to avoid bias in the resulting hypothesis model. Despite the diverse chemical functionalities, the receptor interactions of such molecules are often unexplored. The present study motivates the selection of these molecules diversified by single atom or functional group compared to internal molecules as external set and helps in the understanding of corresponding effects toward receptor interactions and biological endpoints. Applied on anthranilamide-series of factor Xa analogs, the inhibitory activities were correlated (r(2) = 0.99) and validated (q(2) = 0.68) with distance-based pharmacophore descriptors using support vector machine. The selected external set molecules exhibited better prediction accuracy by securing activities less than one residual threshold. The effect on inhibitory activity was assessed by the examination of pharmacophore-similarity and its interactions with key residues of Human factor Xa enzyme using molecular docking approach. Furthermore, qualitative pharmacophore models were developed on the subset of molecular dataset divided as most actives, moderately actives and least actives, to recognize crucial activity governing pharmacophore features. The outcome of this study will bring new insights about the requirements of pharmacophore features and prioritizes its selection in the design and optimization of potent Xa inhibitors.

  6. Modeling Molecular Dynamics from Simulations

    SciTech Connect

    Hinrichs, Nina Singhal

    2009-01-28

    Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical and life sciences. For example, many diseases are caused by protein aggregation or misfolding. One approach to studying these systems is to use physically-based computational simulations to model the interactions and movement of the molecules. While molecular simulations are computationally expensive, it is now possible to simulate many independent molecular dynamics trajectories in a parallel fashion by using super- or distributed- computing methods such as Folding@Home or Blue Gene. The analysis of these large, high-dimensional data sets presents new computational challenges. In this seminar, I will discuss a novel approach to analyzing large ensembles of molecular dynamics trajectories to generate a compact model of the dynamics. This model groups conformations into discrete states and describes the dynamics as Markovian, or history-independent, transitions between the states. I will discuss why the Markovian state model (MSM) is suitable for macromolecular dynamics, and how it can be used to answer many interesting and relevant questions about the molecular system. I will also discuss many of the computational and statistical challenges in building such a model, such as how to appropriately cluster conformations, determine the statistical reliability, and efficiently design new simulations.

  7. Flapping Wing Flight Dynamic Modeling

    DTIC Science & Technology

    2011-08-22

    against those of Theodorsen [16], Garrick [17], Loewy [18], Issacs [19, 20], Greenberg [21], Wagner [22], and von Karman [23] as well as experimental...kinematics and this data was used to generate the nal equations of motion (added to the nonlinear equations already derived from the Newton -Euler...wings). The ight dynamic model is a six-degree-of-freedom set of dynamic equations ( Newton -Euler scheme) with translation described in the inertial

  8. 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

  9. 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.

  10. Definition of an uptake pharmacophore of the serotonin transporter through 3D-QSAR analysis.

    PubMed

    Pratuangdejkul, J; Schneider, B; Jaudon, P; Rosilio, V; Baudoin, E; Loric, S; Conti, M; Launay, J-M; Manivet, P

    2005-01-01

    The serotonergic system plays a critical role in a wide variety of physiological and behavioral processes. Dysregulation of the tightly controlled extracellular concentration of serotonin (5-hydroxytryptamine, 5-HT) appears to be at the origin of a host of metabolic and psychiatric disorders. Since the plasma membrane 5-HT transporter (SERT) is the major protagonist in regulating extracellular 5-HT concentration, SERT is the target of most drugs interacting with the serotonergic system. Unfortunately, some of the drugs towards SERT (e.g. amphetamine derivatives) interfere with cell homeostasis leading to cell toxicity. Developing new SERT ligands devoid of any side-effect represents a major priority in the treatment of 5-HT-associated pathologies. Here, we report structure-activity relationships (SAR) and three-dimensional QSAR (3D-QSAR) studies of a library of 121 compounds including 5-HT analogs, harmanes, benzothiazoles, indanones, amphetamine derivatives and substrate-type 5-HT releasers, with the goal of identifying the structural determinants crucial for SERT uptake. In the absence of data about the bioactive form of 5-HT, conformational analysis of 5-HT was performed using quantum chemistry calculations. This led to three 5-HT stable conformers with anti, -gauche and +gauche side-chain conformation. These conformers, used as templates for superimposition with all the library compounds, enabled the design of a reliable 6-points pharmacophore representative of SERT uptake activity. Molecular dynamics (MD) simulations performed with compounds that are efficiently, moderately, poorly or not transported by SERT allowed to assess the validity of our pharmacophore. Altogether, our data provide for the first time a reliable pharmacophore of SERT uptake activity, which may help to the design of new drugs targeting SERT.

  11. 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.

  12. Pharmacophore mapping of flavone derivatives for aromatase inhibition.

    PubMed

    Nagar, Shuchi; Islam, Md Ataul; Das, Suvadra; Mukherjee, Arup; Saha, Achintya

    2008-02-01

    Aromatase, which catalyses the final step in the steroidogenesis pathway of estrogen, has been target for the design of inhibitor in the treatment of hormone dependent breast cancer for postmenopausal women. The extensive SAR studies performed in the last 30 years to search for potent, selective and less toxic compounds, have led to the development of second and third generation of non-steroidal aromatase inhibitors (AI). Besides the development of synthetic compounds, several naturally occurring and synthetic flavonoids, which are ubiquitous natural phenolic compounds and mediate the host of biological activities, are found to demonstrate inhibitory effects on aromatase. The present study explores the pharmacophores, i.e., the structural requirements of flavones (Fig. 1) for inhibition of aromatase activity, using quantitative structure activity relationship (QSAR) and space modeling approaches. The classical QSAR studies generate the model (R (2) = 0.924, Q (2) = 0.895, s = 0.233) that shows the importance of aromatic rings A and C, along with substitutional requirements in meta and para positions of ring C for the activity. 3D QSAR of Comparative Molecular Field Analysis (CoMFA, R (2) = 0.996, R(2)(cv) = 0.791) and Comparative Molecular Similarity Analysis (CoMSIA, R (2) = 0.992, R(2)(cv) = 0.806) studies show contour maps of steric and hydrophobic properties and contribution of acceptor and donor of the molecule, suggesting the presence of steric hindrance due to ring C and R''-substituent, bulky hydrophobic substitution in ring A, along with acceptors at positions 11, and alpha and gamma of imidazole ring, and donor in ring C favor the inhibitory activity. Further space modeling (CATALYST) study (R = 0.941, Delta( cost ) = 96.96, rmsd = 0.876) adjudge the presence of hydrogen bond acceptor (keto functional group), hydrophobic (ring A) and aromatic rings (steric hindrance) along with critical distance among features are important for the inhibitory activity.

  13. 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.

  14. A Novel Approach for the Identification of Pharmacophores Through Differential Toxicity Analysis of Estrogen Receptor Positive and Negative Cell Lines

    DTIC Science & Technology

    2009-07-01

    Associate Professor of Medicine with a joint appointment as Associate Professor of Pharmacology and Toxicology at the University of Louisville’s...pharmacophores for later 3-D QSAR modeling. Moreover, from a practical point, models of atom size 12 had roughly nearly 200,000 fragments wherein size...performed in general, one can consider the “accuracy” or reproducibility of a standard in vitro toxicological test. For instance, the US National Toxicology

  15. Dynamical models and Galaxy surveys

    NASA Astrophysics Data System (ADS)

    Binney, James; Sanders, Jason L.

    2014-01-01

    Equilibrium dynamical models are essential tools for extracting science from surveys of our Galaxy. We show how models can be tested with data from a survey before the survey's selection function has been determined. We illustrate the application of this method by presenting some results for the RAVE survey. We extend our published analytic distribution functions to include chemistry and fit the chosen functional form to a combination of the Geneva-Copenhagen survey (GCS) and a sample of G-dwarfs observed at z ~ 1.75 kpc by the SEGUE survey. By including solid dynamics we are able to predict the contribution that the thick disc/halo stars surveyed by SEGUE should make to the GCS survey. We show that the measured [Fe/H] distribution from the GCS includes many fewer stars at [Fe/H] < -0.6 than are predicted. The problem is more likely to lie in discordant abundance scales than with incorrect dynamics.

  16. Generative Models of Conformational Dynamics

    PubMed Central

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

  17. 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

  18. The dynamics of coastal models

    USGS Publications Warehouse

    Hearn, Clifford J.

    2008-01-01

    Coastal basins are defined as estuaries, lagoons, and embayments. This book deals with the science of coastal basins using simple models, many of which are presented in either analytical form or Microsoft Excel or MATLAB. The book introduces simple hydrodynamics and its applications, from the use of simple box and one-dimensional models to flow over coral reefs. The book also emphasizes models as a scientific tool in our understanding of coasts, and introduces the value of the most modern flexible mesh combined wave-current models. Examples from shallow basins around the world illustrate the wonders of the scientific method and the power of simple dynamics. This book is ideal for use as an advanced textbook for graduate students and as an introduction to the topic for researchers, especially those from other fields of science needing a basic understanding of the basic ideas of the dynamics of coastal basins.

  19. The incorporation of butyrophenones and related compounds into a pharmacophore for dopamine D2 antagonists.

    PubMed

    Froimowitz, M; Cody, V

    1997-08-01

    This study is an attempt to incorporate the butyrophenones, an important class of nontricyclic antipsychotic drugs, into a previously proposed pharmacophore model of tricyclic dopamine D2 receptor antagonist ligands. Conformational energy calculations were performed using the MM3-92 program on spiperone, as a representative butyrophenone, and milenperone and R48455, as related compounds with more limited conformational freedom. Twenty seven conformers were evaluated for spiperone with MM3-92 calculations and nine of these were within 1.1 kcal/mole of the global minima indicating the flexibility of the compound. A conformational analysis of twenty crystal structures of butyrophenones was also performed and six distinct conformers were represented. All of the energy minimized conformers of spiperone were superimposed in a least squares sense onto loxapine as a relatively rigid, typical D2 antagonist and a pair of mirror image conformers, which are observed in one crystal structure of spiperone, were found to be the best fit. However, it was not possible to discriminate between these two conformers since they fit the pharmacophore model equally well. The para-fluoro and carbonyl group of the butyrophenones were found to correspond best to the oxygen and chlorine atoms of loxapine, respectively. The conformations of milenperone and R48455 were also consistent with the two putative biologically active forms of spiperone and the pharmacophore model. Conformational energy calculations were also performed on molindone, an antipsychotic drug in clinical use, which can be related to the butyrophenones since both have a carbonyl group adjacent to an aromatic ring. A putative biologically active form was proposed for molindone and this was related to the structure of piquindone, a rigid analog of molindone. All of the compounds were found to be entirely consistent with the pharmacophore model. However, as previously found, there is great variability in the distance between the

  20. 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.

  1. 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.

  2. 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.

  3. Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

    PubMed Central

    Liu, Chi; He, Gu; Jiang, Qinglin; Han, Bo; Peng, Cheng

    2013-01-01

    Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents. PMID:23839093

  4. 3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents

    NASA Astrophysics Data System (ADS)

    Andrade, Carolina Horta; Pasqualoto, Kerly F. M.; Ferreira, Elizabeth I.; Hopfinger, Anton J.

    2010-02-01

    Tuberculosis (TB) is the primary cause of mortality among infectious diseases. Mycobacterium tuberculosis monophosphate kinase (TMPKmt) is essential to DNA replication. Thus, this enzyme represents a promising target for developing new drugs against TB. In the present study, the receptor-independent, RI, 4D-QSAR method has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 81 thymidine analogues, and two corresponding subsets, reported as inhibitors of TMPKmt . The resulting optimized models are not only statistically significant with r 2 ranging from 0.83 to 0.92 and q 2 from 0.78 to 0.88, but also are robustly predictive based on test set predictions. The most and the least potent inhibitors in their respective postulated active conformations, derived from each of the models, were docked in the active site of the TMPKmt crystal structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. Moreover, the QSAR models provide insights regarding a probable mechanism of action of the analogues.

  5. Stochastic Model of Microtubule Dynamics

    NASA Astrophysics Data System (ADS)

    Hryniv, Ostap; Martínez Esteban, Antonio

    2017-10-01

    We introduce a continuous time stochastic process on strings made of two types of particle, whose dynamics mimics that of microtubules in a living cell. The long term behaviour of the system is described in terms of the velocity v of the string end. We show that v is an analytic function of its parameters and study its monotonicity properties. We give a complete characterisation of the phase diagram of the model and derive several criteria of the growth (v>0) and the shrinking (v<0) regimes of the dynamics.

  6. Discovery of novel acyl coenzyme a: cholesterol acyltransferase inhibitors: pharmacophore-based virtual screening, synthesis and pharmacology.

    PubMed

    Chhabria, Mahesh T; Brahmkshatriya, Pathik S; Mahajan, Bhushan M; Darji, Urvesh B; Shah, Gaurang B

    2012-07-01

    The present study describes ligand-based pharmacophore modeling of a series of structurally diverse acyl coenzyme A cholesterol acyltransferase inhibitors. Quantitative pharmacophore models were generated using HypoGen module of Discovery Studio 2.1, whereby the best pharmacophore model possessing two hydrophobic, one ring aromatic, and one hydrogen bond acceptor feature for inhibition of acyl coenzyme A cholesterol acyltransferase showed a very good correlation coefficient (r = 0.942) along with satisfactory cost analysis. Hypo1 was also validated by test set and cross-validation methods. Developed models were found to be predictive as indicated by low error values for test set molecules. Virtual screening against Maybridge database using Hypo1 was performed. The two most potent compounds (47 and 48; predicted IC₅₀ = 1 nM) of the retrieved hits were synthesized and biologically evaluated. These compounds showed 86% and 88% inhibition of acyl coenzyme A cholesterol acyltransferase (at 10 μg/mL) with IC₅₀ value of 3.6 and 2.5 nM, respectively. As evident from the close proximity of biological data to the predicted values, it can be concluded that the generated model (Hypo1) is a reliable and useful tool for lead optimization of novel acyl coenzyme A cholesterol acyltransferase inhibitors. © 2012 John Wiley & Sons A/S.

  7. Discovery of N-(2,6-dimethylphenyl)-substituted semicarbazones as anticonvulsants: hybrid pharmacophore-based design.

    PubMed

    Yogeeswari, Perumal; Sriram, Dharmarajan; Thirumurugan, Rathinasabapathy; Raghavendran, Jegadeesan Vaigunda; Sudhan, Kannan; Pavana, Roheeth Kumar; Stables, James

    2005-10-06

    Epilepsy is the most common primary neurological disorder known. In the past decade, various aryl semicarbazones have been designed that were structurally dissimilar from many common anticonvulsants containing the dicarboximide function (CONRCO), which may contribute to toxic side effects. In the present work various N4-(2,6-dimethylphenyl) semicarbazones were designed as pharmacophore hybrids between the aryl semicarbazones and ameltolide. A three-dimensional four-point pharmacophore model was developed for anticonvulsants, and the title compounds were found to match with ralitoline. All of the compounds exhibited anticonvulsant activity in the maximal electroshock test when administered by both intraperitoneal and oral routes. Compound N1-(2,6-dimethylphenyl)-N4-(2-hydroxybenzaldehyde) semicarbazone (9) emerged as a prototype with wide spectrum anticonvulsant agent active in five models of seizure with no neurotoxicity and hepatotoxicity. Compound 9 increased the 4-aminobutyric acid (GABA) level by 118% and inhibited the GABA transaminase enzyme both in vitro and ex vivo.

  8. 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

  9. 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

  10. Virtual screening for SARS-CoV protease based on KZ7088 pharmacophore points.

    PubMed

    Sirois, Suzanne; Wei, Dong-Qing; Du, Qishi; Chou, Kuo-Chen

    2004-01-01

    Pharmacophore modeling can provide valuable insight into ligand-receptor interactions. It can also be used in 3D (dimensional) database searching for potentially finding biologically active compounds and providing new research ideas and directions for drug-discovery projects. To stimulate the structure-based drug design against SARS (severe acute respiratory syndrome), a pharmacophore search was conducted over 3.6 millions of compounds based on the atomic coordinates of the complex obtained by docking KZ7088 (a derivative of AG7088) to SARS CoV M(pro) (coronavirus main proteinase), as reportedly recently (Chou, K. C.; Wei, D. Q.; Zhong, W. Z. Biochem. Biophys. Res. Commun. 2003, 308, 148-151). It has been found that, of the 3.6 millions of compounds screened, 0.07% are with the score satisfying five of the six pharmacophore points. Moreover, each of the hit compounds has been evaluated for druggability according to 13 metrics based on physical, chemical, and structural properties. Of the 0.07% compounds thus retrieved, 17% have a perfect score of 1.0; while 23% with one druggable rule violation, 13% two violations, and 47% more than two violations. If the criterion for druggability is set at a maximum allowance of two rule violations, we obtain that only about 0.03% of the compounds screened are worthy of further tests by experiments. These findings will significantly narrow down the search scope for potential compounds, saving substantial time and money. Finally, the featured templates derived from the current study will also be very useful for guiding the design and synthesis of effective drugs for SARS therapy.

  11. 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.

  12. 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.

  13. Pharmacophore-based design and discovery of (-)-meptazinol carbamates as dual modulators of cholinesterase and amyloidogenesis.

    PubMed

    Xie, Qiong; Zheng, Zhaoxi; Shao, Biyun; Fu, Wei; Xia, Zheng; Li, Wei; Sun, Jian; Zheng, Wei; Zhang, Weiwei; Sheng, Wei; Zhang, Qihong; Chen, Hongzhuan; Wang, Hao; Qiu, Zhuibai

    2017-12-01

    Multifunctional carbamate-type acetylcholinesterase (AChE) inhibitors with anti-amyloidogenic properties like phenserine are potential therapeutic agents for Alzheimer's disease (AD). We reported here the design of new carbamates using pharmacophore model strategy to modulate both cholinesterase and amyloidogenesis. A five-feature pharmacophore model was generated based on 25 carbamate-type training set compounds. (-)-Meptazinol carbamates that superimposed well upon the model were designed and synthesized, which exhibited nanomolar AChE inhibitory potency and good anti-amyloidogenic properties in in vitro test. The phenylcarbamate 43 was highly potent (IC50 31.6 nM) and slightly selective for AChE, and showed low acute toxicity. In enzyme kinetics assay, 43 exhibited uncompetitive inhibition and reacted by pseudo-irreversible mechanism. 43 also showed amyloid-β (Aβ) lowering effects (51.9% decrease of Aβ42) superior to phenserine (31% decrease of total Aβ) in SH-SY5Y-APP695 cells at 50 µM. The dual actions of 43 on cholinergic and amyloidogenic pathways indicated potential uses as symptomatic and disease-modifying agents.

  14. 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.

  15. 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

  16. 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.

  17. Ligand-, structure- and pharmacophore-based molecular fingerprints: a case study on adenosine A1, A2A, A2B, and A3 receptor antagonists

    NASA Astrophysics Data System (ADS)

    Sirci, Francesco; Goracci, Laura; Rodríguez, David; van Muijlwijk-Koezen, Jacqueline; Gutiérrez-de-Terán, Hugo; Mannhold, Raimund

    2012-11-01

    FLAP fingerprints are applied in the ligand-, structure- and pharmacophore-based mode in a case study on antagonists of all four adenosine receptor (AR) subtypes. Structurally diverse antagonist collections with respect to the different ARs were constructed by including binding data to human species only. FLAP models well discriminate "active" (=highly potent) from "inactive" (=weakly potent) AR antagonists, as indicated by enrichment curves, numbers of false positives, and AUC values. For all FLAP modes, model predictivity slightly decreases as follows: A2BR > A2AR > A3R > A1R antagonists. General performance of FLAP modes in this study is: ligand- > structure- > pharmacophore- based mode. We also compared the FLAP performance with other common ligand- and structure-based fingerprints. Concerning the ligand-based mode, FLAP model performance is superior to ECFP4 and ROCS for all AR subtypes. Although focusing on the early first part of the A2A, A2B and A3 enrichment curves, ECFP4 and ROCS still retain a satisfactory retrieval of actives. FLAP is also superior when comparing the structure-based mode with PLANTS and GOLD. In this study we applied for the first time the novel FLAPPharm tool for pharmacophore generation. Pharmacophore hypotheses, generated with this tool, convincingly match with formerly published data. Finally, we could demonstrate the capability of FLAP models to uncover selectivity aspects although single AR subtype models were not trained for this purpose.

  18. Nanomolar anti-sickling compounds identified by ligand-based pharmacophore approach.

    PubMed

    Paz, Odailson Santos; de Jesus Pinheiro, Milena; do Espirito Santo, Renan Fernandes; Villarreal, Cristiane Flora; Castilho, Marcelo Santos

    2017-08-18

    Adenosine receptors are considered as potential targets for drug development against several diseases. The discovery of subtype 2B adenosine receptors role in erythrocyte sickling process proved its importance to neglected diseases such as sickle cell anemia, which affects approximately 29.000 people around the world, but whose treatment is restricted to just one FDA approved drug (hydroxyurea). In order to widen the therapeutic arsenal available to treat sickle cell anemia patients, it is imperative to identify new lead compounds that modify the sickling course and not just its symptoms. In order to accomplish this goal, ligand-based pharmacophore models that differentiate true ligands from decoys and enlighten the structure-activity relationship of known RA2B antagonists were employed screen the lead-like subset of the ZINC database. Following a chemical diversity analysis, 18 compounds were selected for biological evaluation. Among them, one molecule Z1139491704 (pEC50 = 7.77 ± 0.17) has shown better anti-sickling activity than MRS1754 (pEC50 = 7.63 ± 0.12), a commercial RA2B antagonist. Moreover, these compounds exhibited no cytotoxic effect at low micromolar range on mammalian cells. In conclusion, the sound development of validated ligand-based pharmacophore models proved essential to identify novel chemical scaffolds that might be useful to develop anti-sickling drugs. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  19. Towards a Dynamic DES model

    NASA Astrophysics Data System (ADS)

    Subbareddy, Pramod; Candler, Graham

    2009-11-01

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

  20. Evaluation of the pharmacophoric motif of the caged Garcinia xanthones†

    PubMed Central

    Chantarasriwong, Oraphin; Cho, Woo Cheal; Batova, Ayse; Chavasiri, Warinthorn; Moore, Curtis; Rheingold, Arnold L.; Theodorakis, Emmanuel A.

    2010-01-01

    The combination of unique structure and potent bioactivity exhibited by several family members of the caged Garcinia xanthones, led us to evaluate their pharmacophore. We have developed a Pd(0)-catalyzed method for the reverse prenylation of catechols that, together with a Claisen/Diels–Alder reaction cascade, provides rapid and efficient access to various caged analogues. Evaluation of the growth inhibitory activity of these compounds leads to the conclusion that the intact ABC ring system containing the C-ring caged structure is essential to the bioactivity. Studies with cluvenone (7) also showed that these compounds induce apoptosis and exhibit significant cytotoxicity in multidrug-resistant leukemia cells. As such, the caged Garcinia xanthone motif represents a new and potent pharmacophore. PMID:19907779

  1. Modeling Catastrophic Barrier Island Dynamics

    NASA Astrophysics Data System (ADS)

    Whitley, J. W.; McNamara, D.

    2012-12-01

    Barrier islands, thin strips of sand lying parallel to the mainland coastline, along the U.S. Atlantic and Gulf Coasts appear to have maintained their form for thousands of years in the face of rising sea level. The mechanisms that allow barrier islands to remain robust are transport of sediment from the ocean side of barriers to the top and backside during storms, termed island overwash, and the growth and alongshore propagation of tidal deltas near barrier island inlets. Dynamically these processes provide the necessary feedbacks to maintain a barrier island in an attractor that withstands rising sea level within a phase space of barrier island geometrical characteristics. Current barrier island configurations along the Atlantic and Gulf coasts exist among a wide range of storm climate and underlying geologic conditions and therefore the environment that forces overwash and tidal delta dynamics varies considerably. It has been suggested that barrier islands in certain locations such as those between Avon and Buxton (losing 76% of island width since 1852) and Chandeleur islands (losing 85% of its surface area since 2005) along the Atlantic and Gulf coasts, respectively, may be subject to a catastrophic shift in barrier island attractor states - more numerous inlets cutting barriers in some locations and the complete disappearance of barrier islands in other locations. In contrast to common models for barrier islands that neglect storm dynamics and often only consider cross-shore response, we use an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of barrier islands to a wide range of environmental forcing. Results will be presented that show how barrier island attractor states are altered with variations in the rate of sea level rise, storminess, and underlying geology. We will

  2. 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

  3. Common pharmacophore identification using frequent clique detection algorithm.

    PubMed

    Podolyan, Yevgeniy; Karypis, George

    2009-01-01

    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 data set, 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 data sets with arbitrarily large number of conformers per molecule and identify multiple ligand binding modes or multiple binding sites of the target.

  4. 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

  5. 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.

  6. Mathematical Modeling of Wildfire Dynamics

    NASA Astrophysics Data System (ADS)

    Del Bene, Kevin; Drew, Donald

    2012-11-01

    Wildfires have been a long-standing problem in today's society. In this paper, we derive and solve a fluid dynamics model to study a specific type of wildfire, namely, a two dimensional flow around a rising plume above a concentrated heat source, modeling a fire line. This flow assumes a narrow plume of hot gas rising and entraining the surrounding air. The surrounding air is assumed to have constant density and is irrotational far from the fire line. The flow outside the plume is described by a Biot-Savart integral with jump conditions across the position of the plume. The plume model describes the unsteady evolution of the mass, momentum, energy, and vorticity inside the plume, with sources derived to model mixing in the style of Morton, et al. 1956]. The fire is then modeled using a conservation derivation, allowing the fire to propagate, coupling back to the plume model. The results show that this model is capable of capturing the complex interaction of the plume with the surrounding air and fuel layer. Funded by NSF GRFP.

  7. 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

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

    PubMed

    Bavi, Rohit; Kumar, Raj; 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.

  9. Polygamain, a new microtubule depolymerizing agent that occupies a unique pharmacophore in the colchicine site.

    PubMed

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

    2012-03-01

    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 G(2)/M arrest. Polygamain has potent antiproliferative activities against a wide range of cancer cell lines, with an average IC(50) 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.

  10. 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.

  11. Exploring the Influence of the Protein Environment on Metal-Binding Pharmacophores

    PubMed Central

    2015-01-01

    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

  12. 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.

  13. 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.

  14. 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.

  15. 3D pharmacophoric similarity improves multi adverse drug event identification in pharmacovigilance.

    PubMed

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

    2015-03-06

    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.

  16. Modeling the Dynamics of Snags.

    PubMed

    Morrison, Michael L; Raphael, Martin G

    1993-05-01

    Many wildlife species required standing dead trees (i.e., snags) as part of their habitat. Therefore, the ability to predict future density, distribution, and condition of snags can assist resource managers in making land-use decisions. Here we present methods for modeling the dynamics of snags using data from a 10-yr study on the rates of decay, falling, and recruitment of snags on burned and unburned plots in the Sierra Nevada, California. Snags (all species) in advanced stages of decay usually fell within 5 yr, and snags created by fire decayed rapidly and fell quicker (within 10 yr) than those on unburned plots. Pine (Pinus spp.) snags decayed more rapidly than fir (Abies spp.). Although there was an overall net increase in snag density on unburned plots, most of this increase was in the smaller (>13-38 cm diameter at breast height [dbh]) size classes; there was a net decrease in the larger (>38 cm dbh) snags preferred by many birds for nesting and feeding. Overall, snags remained standing the longest that were larger in diameter, shorter in height, less decayed, fir rather than pine, and lacking tops. A Leslie matrix model of snag dynamics predicted changes in snag decay and density only when adjusted for the specific environmental factors(s) causing initial tree mortality. Many snags are created by episodic events, such as fire, disease, drought, and insects. Models of snag dynamics must include the species and condition of trees becoming snags, as well as the factor(s) causing the tree to die. Forest managers must consider this episodic creation of snags when developing snag-management guidelines, and when planning tree-salvage programs based on short-term inventories.

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

    NASA Astrophysics Data System (ADS)

    Biswas, Soham; Sinha, Suman; Sen, Parongama

    2013-08-01

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

  18. Eigenvalue dynamics for multimatrix models

    NASA Astrophysics Data System (ADS)

    de Mello Koch, Robert; Gossman, David; Nkumane, Lwazi; Tribelhorn, Laila

    2017-07-01

    By performing explicit computations of correlation functions, we find evidence that there is a sector of the two matrix model defined by the S U (2 ) sector of N =4 super Yang-Mills theory that can be reduced to eigenvalue dynamics. There is an interesting generalization of the usual Van der Monde determinant that plays a role. The observables we study are the Bogomol'nyi-Prasad-Sommerfield operators of the S U (2 ) sector and include traces of products of both matrices, which are genuine multimatrix observables. These operators are associated with supergravity solutions of string theory.

  19. Bayesian Estimation of Categorical Dynamic Factor Models

    ERIC Educational Resources Information Center

    Zhang, Zhiyong; Nesselroade, John R.

    2007-01-01

    Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…

  20. Bayesian Estimation of Categorical Dynamic Factor Models

    ERIC Educational Resources Information Center

    Zhang, Zhiyong; Nesselroade, John R.

    2007-01-01

    Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…

  1. Characterizing and modeling citation dynamics.

    PubMed

    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.

  2. 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

  3. Dynamical model for competing opinions

    NASA Astrophysics Data System (ADS)

    Souza, S. R.; Gonçalves, S.

    2012-05-01

    We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.

  4. 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.

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

    PubMed

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

    2006-01-01

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

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

    PubMed

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

    2010-09-27

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

  7. 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.

  8. Dynamical model of surrogate reactions

    SciTech Connect

    Aritomo, Y.; Chiba, S.; Nishio, K.

    2011-08-15

    A new dynamical model is developed to describe the whole process of surrogate reactions: Transfer of several nucleons at an initial stage, thermal equilibration of residues leading to washing out of shell effects, and decay of populated compound nuclei are treated in a unified framework. Multidimensional Langevin equations are employed to describe time evolution of collective coordinates with a time-dependent potential energy surface corresponding to different stages of surrogate reactions. The new model is capable of calculating spin distributions of the compound nuclei, one of the most important quantities in the surrogate technique. Furthermore, various observables of surrogate reactions can be calculated, for example, energy and angular distribution of ejectile and mass distributions of fission fragments. These features are important to assess validity of the proposed model itself, to understand mechanisms of the surrogate reactions, and to determine unknown parameters of the model. It is found that spin distributions of compound nuclei produced in {sup 18}O+{sup 238}U{yields}{sup 16}O+{sup 240}*U and {sup 18}O+{sup 236}U{yields}{sup 16}O+{sup 238}*U reactions are equivalent and much less than 10({h_bar}/2{pi}) and therefore satisfy conditions proposed by Chiba and Iwamoto [Phys. Rev. C 81, 044604 (2010)] if they are used as a pair in the surrogate ratio method.

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    PubMed

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

    2015-03-01

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

  13. 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.

  14. Self-organizing neural networks for pharmacophore mapping.

    PubMed

    Polanski, Jaroslaw

    2003-09-12

    We have shown that the SOM network can be a useful tool in pharmacophore mapping strategy. A possibility for the generation of fuzzy molecular representations together with its ability for discovering such aspects of molecular similarity that can be easily overlooked by a human chemist is an important advantage. The reduction in complexity resulting from the data compression is another one. The main disadvantage of SOM usage is the need for the application of special software packages not usually organized in user friendly toolboxes that can be applied easily. Instead, it needs some experience and time to optimize the parameters controlling the performance of the network.

  15. Opinion dynamics model based on quantum formalism

    SciTech Connect

    Artawan, I. Nengah; Trisnawati, N. L. P.

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

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

    PubMed

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

    2017-02-01

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

  17. Synthesis and structure-activity relationships of a new model of arylpiperazines. 5. Study of the physicochemical influence of the pharmacophore on 5-HT(1a)/alpha(1)-adrenergic receptor affinity: synthesis of a new derivative with mixed 5-HT(1a)/d(2) antagonist properties.

    PubMed

    López-Rodríguez, M L; Morcillo, M J; Fernández, E; Porras, E; Orensanz, L; Beneytez, M E; Manzanares, J; Fuentes, J A

    2001-01-18

    In this paper we have designed and synthesized a test series of 32 amide arylpiperazine derivatives VI in order to gain insight into the physicochemical influence of the pharmacophores of 5-HT(1A) and alpha(1)-adrenergic receptors. The training set was designed applying a fractional factorial design using six physicochemical descriptors. The amide moiety is a bicyclohydantoin or a diketopiperazine (X = -(CH(2))(3)-, -(CH(2))(4)-; m = 0, 1), the spacer length is 3 or 4 methylene units, which are the optimum values for both receptors, and the aromatic substituent R occupies the ortho- or meta-position and has been selected from a database of 387 substituents using the EDISFAR program. The 5-HT(1A) and alpha(1)-adrenergic receptor binding affinities of synthesized compounds VI (1-32) have been determined. This data set has been used to derive classical quantitative structure-activity relationships (QSAR) and neural networks models for both receptors (following paper). A comparison of these models gives information for the design of the new ligand EF-7412 (46) (5-HT(1A): K(i) = 27 nM; alpha(1): K(i) > 1000 nM). This derivative displays affinity for the dopamine D(2) receptor (K(i) = 22 nM) and is selective versus all other receptors examined (5-HT(2A), 5-HT(3), 5-HT(4) and Bz; K(i) > 1000 nM). EF-7412 (46) acts as an antagonist in vivo in pre- and postsynaptic 5-HT(1A) receptor sites and as an antagonist in the dopamine D(2) receptor. Thus, EF-7412 (46) is a derivative with mixed 5-HT(1A)/D(2) antagonist properties and this derivative could be useful as a pharmacological tool.

  18. Molecular design based on receptor-independent pharmacophore: application to estrogen receptor ligands.

    PubMed

    Islam, Md Ataul; Nagar, Shuchi; Das, Suvadra; Mukherjee, Arup; Saha, Achintya

    2008-07-01

    Estrogens, a group of steroid hormones, act primarily by regulating gene expression after binding with estrogen receptor (ER), a nuclear ligand-activated transcription factor, translocates to the nucleus after dimer formation, enhances the gene transcription. Estrogen Receptor Modulators (ERMs) have selective agonist and antagonist effects to different tissues, and the purpose of research on ERMs is to identify new potent and less toxic drug molecules. The present study has been focused on finding the structural requirements of ER ligand, using receptor-independent pharmacophore space modeling studies that can explore 3D structural features and configurations, responsible for the biological activity of structurally diverse compounds. The studies show (R=0.945, RMSD=2.186, Deltacost=677.354) the importance of hydrogen bond acceptors in the aromatic rings and a planner hydrophobic region in the molecular architecture along with critical geometrical distance between features are effectively crucial for binding with ER.

  19. The nociceptin pharmacophore site for opioid receptor binding derived from the NMR structure and bioactivity relationships.

    PubMed

    Orsini, Michael J; Nesmelova, Irina; Young, Helen C; Hargittai, Balazs; Beavers, Mary Pat; Liu, Jingchun; Connolly, Peter J; Middleton, Steven A; Mayo, Kevin H

    2005-03-04

    Nociceptin, a 17 amino acid opioid-like peptide that has an inhibitory effect on synaptic transmission in the nervous system, is involved in learning, memory, attention, and emotion and is also implicated in the perception of pain and visual, auditory, and olfactory functions. In this study, we investigated the NMR solution structure of nociceptin in membrane-like environments (trifluoroethanol and SDS micelles) and found it to have a relatively stable helix conformation from residues 4-17 with functionally important N-terminal residues being folded aperidoically on top of the helix. In functional assays for receptor binding and calcium flux, alanine-scanning variants of nociceptin indicated that functionally important residues generally followed helix periodicity, consistent with the NMR structural model. Structure-activity relationships allowed identification of pharmacophore sites that were used in small molecule data base searches, affording hits with demonstrated nociceptin receptor binding affinities.

  20. A genetic algorithm for flexible molecular overlay and pharmacophore elucidation

    NASA Astrophysics Data System (ADS)

    Jones, Gareth; Willett, Peter; Glen, Robert C.

    1995-12-01

    A genetic algorithm (GA) has been developed for the superimposition of sets of flexible molecules. Molecules are represented by a chromosome that encodes angles of rotation about flexible bonds and mappings between hydrogen-bond donor proton, acceptor lone pair and ring centre features in pairs of molecules. The molecule with the smallest number of features in the data set is used as a template, onto which the remaining molecules are fitted with the objective of maximising structural equivalences. The fitness function of the GA is a weighted combination of: (i) the number and the similarity of the features that have been overlaid in this way; (ii) the volume integral of the overlay; and (iii) the van der Waals energy of the molecular conformations defined by the torsion angles encoded in the chromosomes. The algorithm has been applied to a number of pharmacophore elucidation problems, i.e., angiotensin II receptor antagonists, Leu-enkephalin and a hybrid morphine molecule, 5-HT1D agonists, benzodiazepine receptor ligands, 5-HT3 antagonists, dopamine D2 antagonists, dopamine reuptake blockers and FKBP12 ligands. The resulting pharmacophores are generated rapidly and are in good agreement with those derived from alternative means.

  1. Ultrafast de novo docking combining pharmacophores and combinatorics

    NASA Astrophysics Data System (ADS)

    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.

  2. Model dynamics for quantum computing

    NASA Astrophysics Data System (ADS)

    Tabakin, Frank

    2017-08-01

    A model master equation suitable for quantum computing dynamics is presented. In an ideal quantum computer (QC), a system of qubits evolves in time unitarily and, by virtue of their entanglement, interfere quantum mechanically to solve otherwise intractable problems. In the real situation, a QC is subject to decoherence and attenuation effects due to interaction with an environment and with possible short-term random disturbances and gate deficiencies. The stability of a QC under such attacks is a key issue for the development of realistic devices. We assume that the influence of the environment can be incorporated by a master equation that includes unitary evolution with gates, supplemented by a Lindblad term. Lindblad operators of various types are explored; namely, steady, pulsed, gate friction, and measurement operators. In the master equation, we use the Lindblad term to describe short time intrusions by random Lindblad pulses. The phenomenological master equation is then extended to include a nonlinear Beretta term that describes the evolution of a closed system with increasing entropy. An external Bath environment is stipulated by a fixed temperature in two different ways. Here we explore the case of a simple one-qubit system in preparation for generalization to multi-qubit, qutrit and hybrid qubit-qutrit systems. This model master equation can be used to test the stability of memory and the efficacy of quantum gates. The properties of such hybrid master equations are explored, with emphasis on the role of thermal equilibrium and entropy constraints. Several significant properties of time-dependent qubit evolution are revealed by this simple study.

  3. Integration of ligand and structure based approaches for identification of novel MbtI inhibitors in Mycobacterium tuberculosis and molecular dynamics simulation studies.

    PubMed

    Maganti, Lakshmi; Grandhi, Pradeep; Ghoshal, Nanda

    2016-11-01

    Mycobacterium tuberculosis is an obligate pathogen of mammals and is responsible for more than two million deaths annually. The ability to acquire iron from the extracellular environment is a key determinant of pathogenicity in mycobacteria. M. tuberculosis acquires iron exclusively through the siderophores. Several lines of evidence suggest that siderophores have a critical role in bacterial growth and virulence. Hence, in the present study, we have used a combined ligand and structure-based drug design approach for identification of novel inhibitors against salicylate synthase MbtI, a unique and essential enzyme for the biosynthesis of siderophores in M. tuberculosis. We have generated the ligand based and structure based pharmacophores and validated exhaustively. From the validation results it was found that GH (Goodness of Hit) scores for the selected ligand based and structure based pharmacophore models were 0.89 and 0.97, respectively, which indicate that the quality of the pharmacophore models are acceptable as GH value is >0.7. The validated pharmacophores were used for screening the ZINC database. A total of 73 hits, obtained through various insilico screening techniques, were further enriched to 17 hits using docking studies. Molecular dynamics simulations were carried out to compare the binding mode and stability of complexes of MbtI bound with substrate, known inhibitors, and three top ranked hits. The results obtained in this study gave assurance about the identified hits as prospective inhibitors of MbtI.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Addressing Dynamic Issues of Program Model Checking

    NASA Technical Reports Server (NTRS)

    Lerda, Flavio; Visser, Willem

    2001-01-01

    Model checking real programs has recently become an active research area. Programs however exhibit two characteristics that make model checking difficult: the complexity of their state and the dynamic nature of many programs. Here we address both these issues within the context of the Java PathFinder (JPF) model checker. Firstly, we will show how the state of a Java program can be encoded efficiently and how this encoding can be exploited to improve model checking. Next we show how to use symmetry reductions to alleviate some of the problems introduced by the dynamic nature of Java programs. Lastly, we show how distributed model checking of a dynamic program can be achieved, and furthermore, how dynamic partitions of the state space can improve model checking. We support all our findings with results from applying these techniques within the JPF model checker.

  9. 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

  10. Discovery of oxazole and triazole derivatives as potent and selective S1P(1) agonists through pharmacophore-guided design.

    PubMed

    Tian, Yulin; Jin, Jing; Wang, Xiaojian; Hu, Jinping; Xiao, Qiong; Zhou, Wanqi; Chen, Xiaoguang; Yin, Dali

    2014-10-06

    We have discovered a series of triazole/oxazole-containing 2-substituted 2-aminopropane-1,3-diol derivatives as potent and selective S1P1 agonists (prodrugs) based on pharmacophore-guided rational design. Most compounds showed high affinity and selectivity for S1P1 receptor. Compounds 19b, 19d and 19p displayed clear dose responsiveness in the lymphocyte reduction model when administered orally at doses of 0.3, 1.0, 3.0 mg/kg with reduced effect on heart rate. These three compounds were also identified to have favorable pharmacokinetic properties.

  11. Connecting micro dynamics and population distributions in system dynamics models.

    PubMed

    Fallah-Fini, Saeideh; Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2013-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model.

  12. Connecting micro dynamics and population distributions in system dynamics models

    PubMed Central

    Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2014-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

  13. Pharmacophore generation and atom-based 3D-QSAR of novel quinoline-3-carbonitrile derivatives as Tpl2 kinase inhibitors.

    PubMed

    Teli, Mahesh Kumar; Rajanikant, G K

    2012-08-01

    Tumour progression locus-2 (Tpl2) is a serine/threonine kinase, which regulates the expression of tumour necrosis factor α. The article describes the development of a robust pharmacophore model and the investigation of structure-activity relationship analysis of quinoline-3-carbonitrile derivatives reported for Tpl2 kinase inhibition. A five point pharmacophore model (ADRRR) was developed and used to derive a predictive atom-based 3-dimensional quantitative structure activity relationship (3D-QSAR) model. The obtained 3D-QSAR model has an excellent correlation coefficient value (r(2)= 0.96), Fisher ratio (F = 131.9) and exhibited good predictive power (q(2) = 0.79). The QSAR model suggests that the inclusion of hydrophobic substituents will enhance the Tpl2 kinase inhibition. In addition, H-bond donating groups, negative ionic groups and electron withdrawing groups positively contribute to the Tpl2 kinase inhibition. Further, pharmacophoric model was validated by the receiver operating characteristic curve analysis and was employed for virtual screening to identify six potential Tpl2 kinase inhibitors. The findings of this study provide a set of guidelines for designing compounds with better Tpl2 kinase inhibitory potency.

  14. 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.

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

    PubMed

    Ojha, Probir Kumar; Roy, Kunal

    2011-05-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  18. Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

    NASA Astrophysics Data System (ADS)

    Kharkar, Prashant S.; Reith, Maarten E. A.; Dutta, Aloke K.

    2008-01-01

    Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of -OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.

  19. 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.

  20. 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.

  1. 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.

  2. Targeting dynamic pockets of HIV-1 protease by structure-based computational screening for allosteric inhibitors.

    PubMed

    Kunze, Jens; Todoroff, Nickolay; Schneider, Petra; Rodrigues, Tiago; Geppert, Tim; Reisen, Felix; Schreuder, Herman; Saas, Joachim; Hessler, Gerhard; Baringhaus, Karl-Heinz; Schneider, Gisbert

    2014-03-24

    We present the discovery of low molecular weight inhibitors of human immunodeficiency virus 1 (HIV-1) protease subtype B that were identified by structure-based virtual screening as ligands of an allosteric surface cavity. For pocket identification and prioritization, we performed a molecular dynamics simulation and observed several flexible, partially transient surface cavities. For one of these presumable ligand-binding pockets that are located in the so-called "hinge region" of the identical protease chains, we computed a receptor-derived pharmacophore model, with which we retrieved fragment-like inhibitors from a screening compound pool. The most potent hit inhibited protease activity in vitro in a noncompetitive mode of action. Although attempts failed to crystallize this ligand bound to the enzyme, the study provides proof-of-concept for identifying innovative tool compounds for chemical biology by addressing flexible protein models with receptor pocket-derived pharmacophore screening.

  3. Investigation of PDE5/PDE6 and PDE5/PDE11 selective potent tadalafil-like PDE5 inhibitors using combination of molecular modeling approaches, molecular fingerprint-based virtual screening protocols and structure-based pharmacophore development.

    PubMed

    Kayık, Gülru; Tüzün, Nurcan Ş; Durdagi, Serdar

    2017-12-01

    The essential biological function of phosphodiesterase (PDE) type enzymes is to regulate the cytoplasmic levels of intracellular second messengers, 3',5'-cyclic guanosine monophosphate (cGMP) and/or 3',5'-cyclic adenosine monophosphate (cAMP). PDE targets have 11 isoenzymes. Of these enzymes, PDE5 has attracted a special attention over the years after its recognition as being the target enzyme in treating erectile dysfunction. Due to the amino acid sequence and the secondary structural similarity of PDE6 and PDE11 with the catalytic domain of PDE5, first-generation PDE5 inhibitors (i.e. sildenafil and vardenafil) are also competitive inhibitors of PDE6 and PDE11. Since the major challenge of designing novel PDE5 inhibitors is to decrease their cross-reactivity with PDE6 and PDE11, in this study, we attempt to identify potent tadalafil-like PDE5 inhibitors that have PDE5/PDE6 and PDE5/PDE11 selectivity. For this aim, the similarity-based virtual screening protocol is applied for the "clean drug-like subset of ZINC database" that contains more than 20 million small compounds. Moreover, molecular dynamics (MD) simulations of selected hits complexed with PDE5 and off-targets were performed in order to get insights for structural and dynamical behaviors of the selected molecules as selective PDE5 inhibitors. Since tadalafil blocks hERG1 K channels in concentration dependent manner, the cardiotoxicity prediction of the hit molecules was also tested. Results of this study can be useful for designing of novel, safe and selective PDE5 inhibitors.

  4. A potential CARB-pharmacophore for antineoplastic activity: part 1.

    PubMed

    Witczak, Zbigniew J; Poplawski, Tomasz; Czubatka, Anna; Sarnik, Joanna; Tokarz, Pawel; VanWert, Adam L; Bielski, Roman

    2014-04-01

    Diverse functionalized representatives of various classes of sugars, such as thio-, anhydro-, and sulfamido-sugars and myo-inositol oxide, were synthesized and assessed for cytotoxicity against human cancer cell lines (A549, LoVo, MCF-7 and HeLa). The inositol oxide (4) was more active against MCF-7 cells (i.e., an estrogen-dependent breast cancer line), whereas all 3 sulfur-containing compounds showed strongest activity against A549 cells (i.e., a lung adenocarcinoma line). We propose to use a concept of functional 'CARB-pharmacophores' when evaluating a potential for the compounds' general antineoplastic activity. Future studies will determine the reasons for cell-type specificity of these compounds. The thio-sugar motif appears to be a promising lead for future developments. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. 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

  6. Click chemistry: 1,2,3-triazoles as pharmacophores.

    PubMed

    Agalave, Sandip G; Maujan, Suleman R; Pore, Vandana S

    2011-10-04

    The copper(I)-catalyzed 1,2,3-triazole-forming reaction between azides and terminal alkynes has become the gold standard of 'click chemistry' due to its reliability, specificity, and biocompatibility. Applications of click chemistry are increasingly found in all aspects of drug discovery; they range from lead finding through combinatorial chemistry and target-templated in vitro chemistry, to proteomics and DNA research by using bioconjugation reactions. The triazole products are more than just passive linkers; they readily associate with biological targets, through hydrogen-bonding and dipole interactions. The present review will focus mainly on the recent literature for applications of this reaction in the field of medicinal chemistry, in particular on use of the 1,2,3-triazole moiety as pharmacophore.

  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. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

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

    PubMed Central

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

    2007-01-01

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

  14. Dynamic coupling of three hydrodynamic models

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  15. Dynamic Modeling, Chaos, and Cognitive Development.

    ERIC Educational Resources Information Center

    Howe, Mark L.; Rabinowitz, F. Michael

    1994-01-01

    Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…

  16. Dynamic Modeling, Chaos, and Cognitive Development.

    ERIC Educational Resources Information Center

    Howe, Mark L.; Rabinowitz, F. Michael

    1994-01-01

    Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…

  17. Biomolecular dynamics of DNA: statistical mechanics and dynamical models

    NASA Astrophysics Data System (ADS)

    Peyrard, M.; Dauxois, T.; Hoyet, H.; Willis, C. R.

    1993-09-01

    There is a growing feeling that biomolecular structure is not sufficient to determine biological activity which is also governed by large amplitude dynamics of the molecules. The transcription of DNA or its thermal denaturation are typical examples. Traditional approaches use Ising models to describe the denaturation transition of DNA. They have to introduce phenomenological “cooperativity factors” to explain the rather sharp “melting” of this quasi one-dimensional system. We present models which describe the full dynamics of the melting. Using molecular dynamics simulations and statistical analysis, we discuss the mechanism of the denaturation, including precursor effects that can be related to large amplitude localized nonlinear excitations of the molecule in which discreteness effects play a large role. We also show the microscopic origin of the cooperativity factors.

  18. Two-Stage Reduction Of Dynamical Models

    NASA Technical Reports Server (NTRS)

    Lee, Allan Y.; Tsuha, Walter S.

    1993-01-01

    No longer necessary to solve eigenvalue problems of high order. Component-mode projection-and-assembly model-reduction (COMPARE) method provides approximation of dynamics of vibrations of complicated, multiple flexible bodies by use of mathematical models of reduced order. Incorporates component-mode synthesis (CMS) method and enhanced projection-and-assembly (EP&A) method, described in "Enhanced Method of Reduction of Dynamical Models" (NPO-18402), providing for somewhat simplified two-stage process in which order of applicable mathematical models reduced. Reduced-order models used to design algorithms of control systems to suppress vibrations or otherwise control structure.

  19. Design, synthesis, evaluation and molecular modelling studies of some novel 5,6-diphenyl-1,2,4-triazin-3(2H)-ones bearing five-member heterocyclic moieties as potential COX-2 inhibitors: A hybrid pharmacophore approach.

    PubMed

    Banerjee, Anupam G; Das, Nirupam; Shengule, Sushant A; Sharma, Piyoosh A; Srivastava, Radhey Shyam; Shrivastava, Sushant Kumar

    2016-12-01

    A series of novel hybrids comprising of 1,3,4-oxadiazole/thiadiazole and 1,2,4-triazole tethered to 5,6-diphenyl-1,2,4-triazin-3(2H)-one were designed, synthesised and evaluated as COX-2 inhibitors for the treatment of inflammation. The synthesised hybrids were characterised using FT-IR, 1H NMR, 13C NMR, elemental (C,H,N) analyses and assessed for their anti-inflammatory potential by in vitro albumin denaturation assay. Compounds exhibiting activity comparable to indomethacin and celecoxib were further evaluated for in vivo anti-inflammatory activity. Oral administration of promising compounds 3c-3e and 4c-4e did not evoke significant gastric, hepatic and renal toxicity in rats. These potential compounds exhibited reduced malondialdehyde (MDA) content on the gastric mucosa suggesting their protective effects by inhibition of lipid peroxidation. Based on the outcome of in vitro COX assay, compounds 3c-3e and 4c-4e (IC50 0.60-1.11μM) elicited an interesting profile as competitive selective COX-2 inhibitors. Further, selected compounds 3e and 4c were found devoid of cardiotoxicity post evaluation on myocardial infarcted rats. The in silico binding mode of the potential compounds into the COX-2 active site through docking and molecular dynamics exemplified their consensual interaction and subsequent COX-2 inhibition with significant implications for structure-based drug design.

  20. 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

  1. 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.

  2. Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket

    NASA Astrophysics Data System (ADS)

    Drwal, Malgorzata N.; Agama, Keli; Pommier, Yves; Griffith, Renate

    2013-12-01

    Purely structure-based pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.

  3. 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

  4. Automated adaptive inference of phenomenological dynamical models

    NASA Astrophysics Data System (ADS)

    Daniels, Bryan C.; Nemenman, Ilya

    2015-08-01

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

  5. 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.

  6. 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.

  7. Model Verification of Mixed Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Evensen, D. A.; Chrostowski, J. D.; Hasselman, T. K.

    1982-01-01

    MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.

  8. Stochastic population dynamic models as probability networks

    Treesearch

    M.E. and D.C. Lee. Borsuk

    2009-01-01

    The dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and...

  9. A dynamical model of color confinement

    NASA Astrophysics Data System (ADS)

    Loh, S.; Biró, T. S.; Mosel, U.; Thoma, M. H.

    1996-02-01

    A dynamical model of confinement based on a transport theoretical description of the Friedberg-Lee model is extended to explicit color degrees of freedom. The string tension is reproduced by an adiabatic string formation from the nucleon ground state. Color isovector oscillation modes of a qq¯-system are investigated for a wide range of relative qq¯-momenta and the dynamical impact of color confinement on the quark motion is shown.

  10. Approximate dynamic model of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Artemov, O. A.

    1978-01-01

    An approximate dynamic nonlinear model of a turbojet engine is elaborated on as a tool in studying the aircraft control loop, with the turbojet engine treated as an actuating component. Approximate relationships linking the basic engine parameters and shaft speed are derived to simplify the problem, and to aid in constructing an approximate nonlinear dynamic model of turbojet engine performance useful for predicting aircraft motion.

  11. 3D pharmacophore mapping using 4D QSAR analysis for the cytotoxicity of lamellarins against human hormone-dependent T47D breast cancer cells.

    PubMed

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

    2009-10-01

    4D quantitative structure-activity relationship (QSAR) and 3D pharmacophore models were built and investigated for 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 lipophilicity. 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 the formation of an intermolecular hydrogen bond and the 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 with the 4D QSAR models. The optimized 4D QSAR 3D pharmacophore model has a leave-one-out 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

  12. 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

  13. Single timepoint models of dynamic systems

    PubMed Central

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

    2013-01-01

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

  14. Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part II: Identification of enzyme inhibitors from Prasaplai, a Thai traditional medicine

    PubMed Central

    Waltenberger, Birgit; Schuster, Daniela; Paramapojn, Sompol; Gritsanapan, Wandee; Wolber, Gerhard; Rollinger, Judith M.; Stuppner, Hermann

    2011-01-01

    Prasaplai is a medicinal plant mixture that is used in Thailand to treat primary dysmenorrhea, which is characterized by painful uterine contractility caused by a significant increase of prostaglandin release. Cyclooxygenase (COX) represents a key enzyme in the formation of prostaglandins. Former studies revealed that extracts of Prasaplai inhibit COX-1 and COX-2. In this study, a comprehensive literature survey for known constituents of Prasaplai was performed. A multiconformational 3D database was created comprising 683 molecules. Virtual parallel screening using six validated pharmacophore models for COX inhibitors was performed resulting in a hit list of 166 compounds. 46 Prasaplai components with already determined COX activity were used for the external validation of this set of COX pharmacophore models. 57% of these components were classified correctly by the pharmacophore models. These findings confirm that the virtual approach provides a helpful tool (i) to unravel which molecular compounds might be responsible for the COX-inhibitory activity of Prasaplai and (ii) for the fast identification of novel COX inhibitors. PMID:20851587

  15. 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.

  16. 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.

  17. 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.

  18. Discrete model for DNA-promoter dynamics

    NASA Astrophysics Data System (ADS)

    Salerno, Mario

    1991-10-01

    We introduce a discrete model for DNA that takes into account the information about specific base sequences along the double helix. We use this model to study nonlinear wave dynamics of the T7A1 DNA promoter. As results we show the existence in the promoter of a dynamically active region in which static solitons acquire finite velocities, which contrasts with regions where solitons simply remain static. Furthermore, when they pass through this region moving solitons are accelerated, decelerated, or reflected, depending on their initial velocities. The possibility that these dynamical effects play a role in the mechanism of genetic activation is suggested.

  19. 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

  20. Understanding and Modeling Teams As Dynamical Systems

    PubMed Central

    Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

    2017-01-01

    By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

  1. Model systems for single molecule polymer dynamics.

    PubMed

    Latinwo, Folarin; Schroeder, Charles M

    2011-01-01

    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.

  2. Glassy dynamics of kinetically constrained models

    NASA Astrophysics Data System (ADS)

    Ritort, F.; Sollich, P.

    2003-06-01

    We review the use of kinetically constrained models (KCMs) for the study of dynamics in glassy systems. The characteristic feature of KCMs is that they have trivial, often non-interacting, equilibrium behaviour but interesting slow dynamics due to restrictions on the allowed transitions between configurations. The basic question which KCMs ask is therefore how much glassy physics can be understood without an underlying 'equilibrium glass transition'. After a brief review of glassy phenomenology, we describe the main model classes, which include spin-facilitated (Ising) models, constrained lattice gases, models inspired by cellular structures such as soap froths, models obtained via mappings from interacting systems without constraints, and finally related models such as urn, oscillator, tiling and needle models. We then describe the broad range of techniques that have been applied to KCMs, including exact solutions, adiabatic approximations, projection and mode-coupling techniques, diagrammatic approaches and mappings to quantum systems or effective models. Finally, we give a survey of the known results for the dynamics of KCMs both in and out of equilibrium, including topics such as relaxation time divergences and dynamical transitions, nonlinear relaxation, ageing and effective temperatures, cooperativity and dynamical heterogeneities, and finally non-equilibrium stationary states generated by external driving. We conclude with a discussion of open questions and possibilities for future work.

  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. 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

  5. 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.

  6. 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.

  7. Multi-scale modelling and dynamics

    NASA Astrophysics Data System (ADS)

    Müller-Plathe, Florian

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

  8. Dynamic landscape models of coevolutionary games.

    PubMed

    Richter, Hendrik

    2017-02-24

    Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling procedure is carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use either birth-death (BD) or death-birth (DB) strategy updating. The main focus is on using dynamic fitness landscapes as a mathematical model of coevolutionary game dynamics. Hence, an alternative tool for analyzing coevolutionary games becomes available, and landscape measures such as modality, ruggedness and information content can be computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the interaction networks are calculated numerically. Relations are established between landscape properties expressed by landscape measures and quantifiers of coevolutionary game dynamics such as fixation probabilities, fixation times and network properties.

  9. 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.

  10. 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.

  11. Discovery of nonsteroidal 17beta-hydroxysteroid dehydrogenase 1 inhibitors by pharmacophore-based screening of virtual compound libraries.

    PubMed

    Schuster, Daniela; Nashev, Lyubomir G; Kirchmair, Johannes; Laggner, Christian; Wolber, Gerhard; Langer, Thierry; Odermatt, Alex

    2008-07-24

    17Beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) plays a pivotal role in the local synthesis of the most potent estrogen estradiol. Its expression is a prognostic marker for the outcome of patients with breast cancer and inhibition of 17beta-HSD1 is currently under consideration for breast cancer prevention and treatment. We aimed to identify nonsteroidal 17beta-HSD1 inhibitor scaffolds by virtual screening with pharmacophore models built from crystal structures containing steroidal compounds. The most promising model was validated by comparing predicted and experimentally determined inhibitory activities of several flavonoids. Subsequently, a virtual library of nonsteroidal compounds was screened against the 3D pharmacophore. Analysis of 14 selected compounds yielded four that inhibited the activity of human 17beta-HSD1 (IC 50 below 50 microM). Specificity assessment of identified 17beta-HSD1 inhibitors emphasized the importance of including related short-chain dehydrogenase/reductase (SDR) members to analyze off-target effects. Compound 29 displayed at least 10-fold selectivity over the related SDR enzymes tested.

  12. Quantitative bioactivity prediction and pharmacophore identification for benzotriazine derivatives using the electron conformational-genetic algorithm in QSAR.

    PubMed

    Sahin, K; Sarıpınar, E; Yanmaz, E; Geçen, N

    2011-06-01

    The electron conformational-genetic algorithm (EC-GA), a sophisticated hybrid approach combining the GA and EC methods, has been employed for a 4D-QSAR procedure to identify the pharmacophore for benzotriazines as sarcoma inhibitors and for quantitative prediction of activity. The calculated geometry and electronic structure parameters of every atom and bond of each molecule are arranged in a matrix described as the electron-conformational matrix of contiguity (ECMC). By comparing the ECMC of one of the most active compounds with other ECMCs we were able to obtain the features of the pharmacophore responsible for the activity, as submatrices of the template known as electron conformational submatrices of activity. The GA was used to select the most important descriptors and to predict the theoretical activity of training and test sets. The predictivity of the model was internally validated. The best QSAR model was selected, having r² = 0.9008, standard error = 0.0510 and cross-validated squared correlation coefficient, q² = 0.8192.

  13. Identification of New Human Malaria Parasite Plasmodium Falciparum Dihydroorotate Dehydrogenase Inhibitors by Pharmacophore and Structure-Based Virtual Screening

    PubMed Central

    Pavadai, Elumalai; El Mazouni, Farah; Wittlin, Sergio; de Kock, Carmen; Phillips, Margaret A.; Chibale, Kelly

    2016-01-01

    Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH), a key enzyme in the de novo pyrimidine biosynthesis pathway, which the Plasmodium falciparum relies on exclusively for survival, has emerged as a promising target for antimalarial drugs. In an effort to discover new and potent PfDHODH inhibitors, 3D-QSAR pharmacophore models were developed based on the structures of known PfDHODH inhibitors and the validated Hypo1 model was used as a 3D search query for virtual screening of the National Cancer Institute database. The virtual hit compounds were further filtered based on molecular docking and Molecular Mechanics/Generalized Born Surface Area binding energy calculations. The combination of the pharmacophore and structure-based virtual screening resulted in the identification of nine new compounds that showed >25% inhibition of PfDHODH at a concentration of 10 μM, three of which exhibited IC50 values in the range of 0.38–20 μM. The most active compound, NSC336047, displayed species-selectivity for PfDHODH over human DHODH and inhibited parasite growth with an IC50 of 26 μM. In addition to this, thirteen compounds inhibited parasite growth with IC50 values of ≤ 50 μM, four of which showed IC50 values in the range of 5–12 μM. These compounds could be further explored in the identification and development of more potent PfDHODH and parasite growth inhibitors. PMID:26915022

  14. Identification of New Human Malaria Parasite Plasmodium falciparum Dihydroorotate Dehydrogenase Inhibitors by Pharmacophore and Structure-Based Virtual Screening.

    PubMed

    Pavadai, Elumalai; El Mazouni, Farah; Wittlin, Sergio; de Kock, Carmen; Phillips, Margaret A; Chibale, Kelly

    2016-03-28

    Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH), a key enzyme in the de novo pyrimidine biosynthesis pathway, which the Plasmodium falciparum relies on exclusively for survival, has emerged as a promising target for antimalarial drugs. In an effort to discover new and potent PfDHODH inhibitors, 3D-QSAR pharmacophore models were developed based on the structures of known PfDHODH inhibitors and the validated Hypo1 model was used as a 3D search query for virtual screening of the National Cancer Institute database. The virtual hit compounds were further filtered based on molecular docking and Molecular Mechanics/Generalized Born Surface Area binding energy calculations. The combination of the pharmacophore and structure-based virtual screening resulted in the identification of nine new compounds that showed >25% inhibition of PfDHODH at a concentration of 10 μM, three of which exhibited IC50 values in the range of 0.38-20 μM. The most active compound, NSC336047, displayed species-selectivity for PfDHODH over human DHODH and inhibited parasite growth with an IC50 of 26 μM. In addition to this, 13 compounds inhibited parasite growth with IC50 values of ≤ 50 μM, 4 of which showed IC50 values in the range of 5-12 μM. These compounds could be further explored in the identification and development of more potent PfDHODH and parasite growth inhibitors.

  15. Dynamic stiffness model of spherical parallel robots

    NASA Astrophysics Data System (ADS)

    Cammarata, Alessandro; Caliò, Ivo; D`Urso, Domenico; Greco, Annalisa; Lacagnina, Michele; Fichera, Gabriele

    2016-12-01

    A novel approach to study the elastodynamics of Spherical Parallel Robots is described through an exact dynamic model. Timoshenko arches are used to simulate flexible curved links while the base and mobile platforms are modelled as rigid bodies. Spatial joints are inherently included into the model without Lagrangian multipliers. At first, the equivalent dynamic stiffness matrix of each leg, made up of curved links joined by spatial joints, is derived; then these matrices are assembled to obtain the Global Dynamic Stiffness Matrix of the robot at a given pose. Actuator stiffness is also included into the model to verify its influence on vibrations and modes. The latter are found by applying the Wittrick-Williams algorithm. Finally, numerical simulations and direct comparison to commercial FE results are used to validate the proposed model.

  16. Dynamic centrifugal compressor model for system simulation

    NASA Astrophysics Data System (ADS)

    Jiang, Wei; Khan, Jamil; Dougal, Roger A.

    A dynamic model of a centrifugal compressor capable of system simulation in the virtual test bed (VTB) computational environment is presented. The model is based on first principles, i.e. the dynamic performance including the losses is determined from the compressor geometry and not from the experimentally determined characteristic performance curves. In this study, the compressor losses, such as incidence and friction losses, etc., are mathematically modeled for developing compressor characteristics. For easy implementation in the VTB platform, the non-linear governing equations are discretized in resistive companion (RC) form. The developed simulation model can be applied to virtually any centrifugal compressor. By interfacing with a composite system, such as a Brayton cycle gas turbine, or a fuel cell, the compressor dynamic performance can be evaluated. The surge line for the compressor can also be determined from the simulation results. Furthermore, the model presented here provides a valuable tool for evaluating the system performance as a function of various operating parameters.

  17. 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

  18. Integrated dynamics modeling for supercavitating vehicle systems

    NASA Astrophysics Data System (ADS)

    Kim, Seonhong; Kim, Nakwan

    2015-06-01

    We have performed integrated dynamics modeling for a supercavitating vehicle. A 6-DOF equation of motion was constructed by defining the forces and moments acting on the supercavitating body surface that contacted water. The wetted area was obtained by calculating the cavity size and axis. Cavity dynamics were determined to obtain the cavity profile for calculating the wetted area. Subsequently, the forces and moments acting on each wetted part-the cavitator, fins, and vehicle body-were obtained by physical modeling. The planing force-the interaction force between the vehicle transom and cavity wall-was calculated using the apparent mass of the immersed vehicle transom. We integrated each model and constructed an equation of motion for the supercavitating system. We performed numerical simulations using the integrated dynamics model to analyze the characteristics of the supercavitating system and validate the modeling completeness. Our research enables the design of high-quality controllers and optimal supercavitating systems.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Dynamics modeling and simulation of flexible airships

    NASA Astrophysics Data System (ADS)

    Li, Yuwen

    The resurgence of airships has created a need for dynamics models and simulation capabilities of these lighter-than-air vehicles. The focus of this thesis is a theoretical framework that integrates the flight dynamics, structural dynamics, aerostatics and aerodynamics of flexible airships. The study begins with a dynamics model based on a rigid-body assumption. A comprehensive computation of aerodynamic effects is presented, where the aerodynamic forces and moments are categorized into various terms based on different physical effects. A series of prediction approaches for different aerodynamic effects are unified and applied to airships. The numerical results of aerodynamic derivatives and the simulated responses to control surface deflection inputs are verified by comparing to existing wind-tunnel and flight test data. With the validated aerodynamics and rigid-body modeling, the equations of motion of an elastic airship are derived by the Lagrangian formulation. The airship is modeled as a free-free Euler-Bernoulli beam and the bending deformations are represented by shape functions chosen as the free-free normal modes. In order to capture the coupling between the aerodynamic forces and the structural elasticity, local velocity on the deformed vehicle is used in the computation of aerodynamic forces. Finally, with the inertial, gravity, aerostatic and control forces incorporated, the dynamics model of a flexible airship is represented by a single set of nonlinear ordinary differential equations. The proposed model is implemented as a dynamics simulation program to analyze the dynamics characteristics of the Skyship-500 airship. Simulation results are presented to demonstrate the influence of structural deformation on the aerodynamic forces and the dynamics behavior of the airship. The nonlinear equations of motion are linearized numerically for the purpose of frequency domain analysis and for aeroelastic stability analysis. The results from the latter for the

  4. Discovery of high affinity ligands for β2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking.

    PubMed

    Yakar, Ruya; Akten, Ebru Demet

    2014-09-01

    Novel high affinity compounds for human β2-adrenergic receptor (β2-AR) were searched among the clean drug-like subset of ZINC database consisting of 9,928,465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of β2-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model, a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly, 7.3% of the ZINC database subset (729,413 compounds) satisfied the pharmacophore requirements, along with 44 antagonists and 17 agonists. Afterwards, all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment, the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties, 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known Ki values. Moreover, novel chemical compounds with distinct structures have been determined as potential β2-AR drug candidates.

  5. 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.

  6. 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

  7. Conformation depends on 4D-QSAR analysis using EC-GA method: pharmacophore identification and bioactivity prediction of TIBOs as non-nucleoside reverse transcriptase inhibitors.

    PubMed

    Akyüz, Lalehan; Sarıpınar, Emin

    2013-08-01

    The electron conformational and genetic algorithm methods (EC-GA) were integrated for the identification of the pharmacophore group and predicting the anti HIV-1 activity of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives. To reveal the pharmacophore group, each conformation of all compounds was arranged by electron conformational matrices of congruity. Multiple comparisons of these matrices, within given tolerances for high active and low active TIBO derivatives, allow the identification of the pharmacophore group that refers to the electron conformational submatrix of activity. The effects of conformations, internal and external validation were investigated by four different models based on an ensemble of conformers and a single conformer, both with and without a test set. Model 1 using an ensemble of conformers for the training (39 compounds) and test sets (13 compounds), obtained by the optimum seven parameters, gave satisfactory results (R²(training) = 0.878, R²(test)= 0.910, q² = 0.840, q²(ext1) = 0.926 and q²(ext2) = 0.900).

  8. Determinants of volatile general anesthetic potency: a preliminary three-dimensional pharmacophore for halogenated anesthetics.

    PubMed

    Sewell, Jason C; Sear, John W

    2006-03-01

    We investigated the molecular basis for the immobilizing activity of halogenated volatile anesthetics using comparative molecular field analysis. In vivo potency data (expressed as minimum alveolar concentrations) for 69 structurally diverse anesthetics were obtained from the literature. The drugs were randomly divided into a training set (n = 52) used to derive the activity model and a test set (n = 17) used to independently assess the model's predictive power. The anesthetic structures were aligned so as to maximize their similarity in molecular shape and electrostatic potential to the most potent drug in the group, CF2H-(CF2)3-CH2OH. The conformers and alignments of the anesthetics with maximum similarity (calculated as Carbo indices) were retained and used to derive the comparative molecular field analysis models. The final model explained 94.2% of the variance in the observed activities of the training set compounds. The model showed good predictive capability for both the training set (cross-validated r2 = 0.705) and randomly excluded test set anesthetics (r2 = 0.837). Three-dimensional pharmacophoric maps were derived to identify the spatial distribution of key areas where steric and electrostatic interactions are important in determining immobilizing activity of the halogenated drugs and were compared with our previously published maps obtained for nonhalogenated volatile anesthetics.

  9. Component testing for dynamic model verification

    NASA Technical Reports Server (NTRS)

    Hasselman, T. K.; Chrostowski, J. D.

    1984-01-01

    Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.

  10. 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.

  11. 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.

  12. Dynamical modelling of coordinated multiple robot systems

    NASA Technical Reports Server (NTRS)

    Hayati, Samad

    1987-01-01

    The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.

  13. Dynamics Simulation Model for Space Tethers

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  14. A stochastic evolutionary model for survival dynamics

    NASA Astrophysics Data System (ADS)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2014-09-01

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

  15. Dynamical effects of overparametrization in nonlinear models

    NASA Astrophysics Data System (ADS)

    Aguirre, Luis Antonio; Billings, S. A.

    1995-01-01

    This paper is concemed with dynamical reconstruction for nonlinear systems. The effects of the driving function and of the complexity of a given representation on the bifurcation patter are investigated. It is shown that the use of different driving functions to excite the system may yield models with different bifurcation patterns. The complexity of the reconstructions considered is quantified by the embedding dimension and the number of estimated parameters. In this respect it appears that models which reproduce the original bifurcation behaviour are of limited complexity and that excessively complex models tend to induce ghost bifurcations and spurious dynamical regimes. Moreover, some results suggest that the effects of overparametrization on the global dynamical behaviour of a nonlinear model may be more deleterious than the presence of moderate noise levels. In order to precisely quantify the complexity of the reconstructions, global polynomials are used although the results are believed to apply to a much wider class of representations including neural networks.

  16. Conformer and pharmacophore based identification of peptidomimetic inhibitors of chikungunya virus nsP2 protease.

    PubMed

    Dhindwal, Sonali; Kesari, Pooja; Singh, Harvijay; Kumar, Pravindra; Tomar, Shailly

    2016-12-02

    Chikungunya virus nsP2 replication protein is a cysteine protease, which cleaves the nonstructural nsP1234 polyprotein into functional replication components. The cleavage and processing of nsP1234 by nsP2 protease is essential for the replication and proliferation of the virus. Thus, ChikV nsP2 protease is a promising target for antiviral drug discovery. In this study, the crystal structure of the C-terminal domain of ChikV nsP2 protease (PDB ID: 4ZTB) was used for structure based identification and rational designing of peptidomimetic inhibitors against nsP2 protease. The interactions of the junction residues of nsP3/4 polyprotein in the active site of nsP2 protease have been mimicked to identify and design potential inhibitory molecules. Molecular docking of the nsP3/4 junction peptide in the active site of ChikV nsP2 protease provided the structural insight of the probable binding mode of nsP3/4 peptide and pigeonholed the molecular interactions critical for the substrate binding. Further, the shape and pharmacophoric properties of the viral nsP3/4 substrate peptide were taken into consideration and the mimetic molecules were identified and designed. The designed mimetic compounds were then analyzed by docking and their binding affinity was assessed by molecular dynamics simulations.

  17. A system dynamics model for communications networks

    NASA Astrophysics Data System (ADS)

    Awcock, A. J.; King, T. E. G.

    1985-09-01

    An abstract model of a communications network in system dynamics terminology is developed as implementation of this model by a FORTRAN program package developed at RSRE is discussed. The result of this work is a high-level simulation package in which the performance of adaptive routing algorithms and other network controls may be assessed for a network of arbitrary topology.

  18. Magnetospheric dynamics from a low-dimensional nonlinear dynamics model

    NASA Astrophysics Data System (ADS)

    Doxas, I.; Horton, W.

    1999-05-01

    A physics based model for the coupled solar WIND-Magnetosphere-Ionosphere system (WINDMI) is described. The model is based on truncated descriptions of the collisionless microscopic energy transfer processes occurring in the quasineutral layer, and includes a thermal flux limit neglected in the Magnetohydrodynamic (MHD) closure of the moment equations. All dynamically relevant parameters of the model can be computed analytically. The system is both Kirchhoffian and Hamiltonian, ensuring that the power input from the solar wind is divided into physically realizable energy sub-components, a property not shared by data-based filters. The model provides a consistent mathematical formalism in which different models of the solar wind driver, ionospheric dissipation, global field configuration, and substorm trigger mechanism can be inserted, and the coupling between the different parts of the system investigated.

  19. Adaptation dynamics of the quasispecies model

    NASA Astrophysics Data System (ADS)

    Jain, Kavita

    2009-02-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  20. A dynamical model for the Utricularia trap

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2009-12-01

    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. 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 alpha (ERalpha), 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. 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. The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery.

  2. 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

  3. 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. Copyright (c) 2009. Published by Elsevier Ltd.

  4. 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

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

    PubMed

    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

    2011-11-15

    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.

  6. Automated dynamic analytical model improvement

    NASA Technical Reports Server (NTRS)

    Berman, A.

    1981-01-01

    A method is developed and illustrated which finds minimum changes in analytical mass and stiffness matrices to make them consistent with a set of measured normal modes and natural frequencies. The corrected model is an improved base for studies of physical changes, changes in boundary conditions, and for prediction of forced responses. Features of the method are: efficient procedures not requiring solutions of the eigenproblem; the model may have more degrees of freedom than the test data; modal displacements at all the analytical degrees of freedom are obtained; the frequency dependence of the coordinate transformations are properly treated.

  7. 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

  8. Modeling hybrid perovskites by molecular dynamics.

    PubMed

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  9. Modeling hybrid perovskites by molecular dynamics

    NASA Astrophysics Data System (ADS)

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  10. 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.

  11. 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.

  12. Modelling Martian surface channel dynamics

    NASA Astrophysics Data System (ADS)

    Coulthard, T. J.; Skinner, C.; Kim, J.; Schumann, G.; Neal, J. C.; Bates, P. D.

    2014-12-01

    Extensive and large surface channel features found at Athabasca and Kasei have previously been attributed to the erosional power of flowing water with palaeoflood discharges being estimated from the surface channel dimensions. However, in order for these channels to be alluvial there are several basic questions to be answered. Are water flows under Martian conditions capable of eroding the amounts of sediment required to leave these channels? Are our present estimates of palaeoflood discharge of correct magnitude to carry out this erosion? And are the channels a product of one or many flood events? Here, we use a numerical model (CAESAR-Lisflood) that links a two-dimensional hydrodynamic flow scheme to a sediment transport model to simulate fluvial morphodynamics in the Athabasca and Kasei regions. CAESAR-Lisflood has been successfully applied to simulating flooding, erosion and deposition on Earth in a number of locations, and allows the development of channels, bars, braids and other fluvial features to be modelled. The numerical scheme of the model was adapted to Martian conditions by adjusting gravity, drag co-efficient, roughness and grainsize terms. Preliminary findings indicate that fluvial erosion and deposition is capable of creating mega channel features found at these sites and that existing palaeflood estimates are commensurate with channel forming discharges for these features.

  13. Predicting dynamic topography from mantle circulation models

    NASA Astrophysics Data System (ADS)

    Webb, Peter; Davies, J. Huw

    2013-04-01

    Dynamic topography is anomalous vertical motions of Earth's surface associated with viscous flow in the mantle. Deformable boundaries, such as the surface, CMB and phase transition boundaries, within a fluid (Earth's mantle) are deflected by viscous flow. Denser than average, sinking mantle creates inward deflections of Earth's surface. Equally, upwelling flow creates bulges in the surface; large plumes are commonly thought to produce superswells, such as the anomalously high elevation of Southern Africa. Dynamic topography appears to operate on a number of length scales. Mantle density anomalies estimated from seismic tomography indicate long wavelength dynamic topography at present day of around 2 km amplitude (e.g. Conrand & Husson, 2009) whilst continental scale studies suggest vertical motions of a few hundred metres. Furthermore, time scales must be an important factor to consider when assessing dynamic topography. Stable, dense lower mantle 'piles' may contribute to dynamic surface topography; as they appear stable over reasonably long time scales, long wavelength dynamic topography may be a fairly constant feature over the recent geological past. Shorter wavelength, smaller amplitude dynamic topography may be due to more transient features of mantle convection. Studies on a continental scale reveal shorter term changes in dynamic topography of the order of a few hundred metres (e.g. Roberts & White, 2010; Heine et al., 2010). Understanding dynamic topography is complicated by the fact it is difficult to observe as the signal is often masked by isostatic effects. We use forward mantle convection models with 300 million years of recent plate motion history as the surface boundary condition to generate a present day distribution of density anomalies associated with subducted lithosphere. From the modelled temperature and density fields we calculate the normal stress at or near the surface of the model. As the models generally have a free slip surface where no

  14. Application of electron conformational-genetic algorithm approach to 1,4-dihydropyridines as calcium channel antagonists: pharmacophore identification and bioactivity prediction.

    PubMed

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

    2012-01-01

    Two different approaches, namely the electron conformational and genetic algorithm methods (EC-GA), were combined to identify a pharmacophore group and to predict the antagonist activity of 1,4-dihydropyridines (known calcium channel antagonists) from molecular structure descriptors. To identify the pharmacophore, electron conformational matrices of congruity (ECMC)-which include atomic charges as diagonal elements and bond orders and interatomic distances as off-diagonal elements-were arranged for all compounds. The ECMC of the compound with the highest activity was chosen as a template and compared with the ECMCs of other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA) that refers to the pharmacophore. The genetic algorithm was employed to search for the best subset of parameter combinations that contributes the most to activity. Applying the model with the optimum 10 parameters to training (50 compounds) and test (22 compounds) sets gave satisfactory results (R(2)(training)= 0.848, R(2)(test))= 0.904, with a cross-validated q(2) = 0.780).

  15. 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.

  16. 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.

  17. 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.

  18. Continuous Time Dynamic Topic Models

    DTIC Science & Technology

    2008-06-20

    called topics, can be used to explain the observed collection. LDA is a probabilistic extension of latent semantic indexing (LSI) [5] and probabilistic... latent semantic indexing (pLSI) [11]. Owing to its formal generative semantics, LDA has been extended and applied to authorship [19], email [15...Steyvers. Probabilistic topic models. In Latent Semantic Analysis: A Road to Meaning. 2006. [9] T. L. Griffiths and M. Steyvers. Finding scientific

  19. Feature Extraction for Structural Dynamics Model Validation

    SciTech Connect

    Farrar, Charles; Nishio, Mayuko; Hemez, Francois; Stull, Chris; Park, Gyuhae; Cornwell, Phil; Figueiredo, Eloi; Luscher, D. J.; Worden, Keith

    2016-01-13

    As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

  20. Information Dynamics in Networks: Models and Algorithms

    DTIC Science & Technology

    2016-09-13

    the economics and computer science communities . Such a model of externality is motivated by several factors: • The physical effect of the number of...Information Dynamics in Networks: Models and Algorithms In this project, we investigated how network structure interplays with higher level processes in...online social networks. We investigated the appropriateness of existing mathematical models for explaining the structure of retweet cascades on

  1. Dynamic river basin water quality model

    SciTech Connect

    Yearsley, J.

    1991-09-01

    RBM10 is a river basin model for simulating the dynamics of an aquatic ecosystem which has freely-flowing river reaches, river-run reservoirs, and vertically stratified reservoirs. An Eulerian viewpoint is adopted for solving the conservation equations for temperature, dissolved oxygen, nutrients, phytoplankton, bacteria and conservative constituents. The report describes the model development and the computer program which implements the mathematical model.

  2. Modelling and control of HIV dynamics.

    PubMed

    Landi, Alberto; Mazzoldi, Alberto; Andreoni, Chiara; Bianchi, Matteo; Cavallini, Andrea; Laurino, Marco; Ricotti, Leonardo; Iuliano, Rodolfo; Matteoli, Barbara; Ceccherini-Nelli, Luca

    2008-02-01

    Various models of HIV infection and evolution have been considered in the literature. This paper considers a variant of the Wodarz and Nowak mathematical model, adding "aggressiveness" as a new state variable in order to quantify the strength of the virus and its response to drugs. Although the model proposed is relatively simple, simulation results suggest that it may be useful in predicting the impact of the effectiveness of therapy on HIV dynamics.

  3. The dynamic model of enterprise revenue management

    NASA Astrophysics Data System (ADS)

    Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.

    2017-01-01

    The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.

  4. Dynamic exponents for potts model cluster algorithms

    NASA Astrophysics Data System (ADS)

    Coddington, Paul D.; Baillie, Clive F.

    We have studied the Swendsen-Wang and Wolff cluster update algorithms for the Ising model in 2, 3 and 4 dimensions. The data indicate simple relations between the specific heat and the Wolff autocorrelations, and between the magnetization and the Swendsen-Wang autocorrelations. This implies that the dynamic critical exponents are related to the static exponents of the Ising model. We also investigate the possibility of similar relationships for the Q-state Potts model.

  5. 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.

  6. 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

  7. A dynamic conceptual model of care planning.

    PubMed

    Elf, Marie; Poutilova, Maria; Ohrn, Kerstin

    2007-12-01

    This article presents a conceptual model of the care planning process developed to identify the hypothetical links between structural, process and outcome factors important to the quality of the process. Based on existing literature, it was hypothesized that a thorough assessment of patients' health needs is an important prerequisite when making a rigorous diagnosis and preparing plans for various care interventions. Other important variables that are assumed to influence the quality of the process are the care culture and professional knowledge. The conceptual model was developed as a system dynamics causal loop diagram as a first essential step towards a computed model. System dynamics offers the potential to describe processes in a nonlinear, dynamic way and is suitable for exploring, comprehending, learning and communicating complex ideas about care processes.

  8. Dynamic Smagorinsky model on anisotropic grids

    NASA Technical Reports Server (NTRS)

    Scotti, A.; Meneveau, C.; Fatica, M.

    1996-01-01

    Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.

  9. Dynamic reliability models with conditional proportional hazards.

    PubMed

    Hollander, M; Peña, E A

    1995-01-01

    A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a 'jump' from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution function of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.

  10. 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.

  11. 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.

  12. 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.

  13. Dynamic models of Fabry-Perot interferometers.

    PubMed

    Redding, David; Regehr, Martin; Sievers, Lisa

    2002-05-20

    Long-baseline, high-finesse Fabry-Perot interferometers can be used to make distance measurements that are precise enough to detect gravity waves. This level of sensitivity is achieved in part when the interferometer mirrors are isolated dynamically, with pendulum mounts and high-bandwidth cavity length control servos to reduce the effects of seismic noise. We present dynamical models of the cavity fields and signals of Fabry-Perot interferometers for use in the design and evaluation of length control systems for gravity-wave detectors. Models are described and compared with experimental data.

  14. Dynamical properties of the Rabi model

    NASA Astrophysics Data System (ADS)

    Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin

    2017-02-01

    We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation.

  15. Robot arm dynamic model reduction for control

    NASA Technical Reports Server (NTRS)

    Bejczy, A. K.; Lee, S.

    1983-01-01

    General methods are described by which the mathematical complexities of explicit and exact state equations of robot arms can be reduced to a simplified and compact state equation representation without introducing significant errors into the robot arm dynamic model. The model reduction methods are based on homogeneous coordinates and on the Langrangian algorithm for robot arm dynamics, and utilize matrix, vector and numeric analysis techniques. The derivation of differential vector representation of centripetal and Coriolis forces which has not yet been established in the literature is presented.

  16. Quantum model for the price dynamics

    NASA Astrophysics Data System (ADS)

    Choustova, Olga

    2008-10-01

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

  17. An integrated model of Plasmodium falciparum dynamics.

    PubMed

    McKenzie, F Ellis; Bossert, William H

    2005-02-07

    The within-host and between-host dynamics of malaria are linked in myriad ways, but most obviously by gametocytes, the parasite blood forms transmissible from human to mosquito. Gametocyte dynamics depend on those of non-transmissible blood forms, which stimulate immune responses, impeding transmission as well as within-host parasite densities. These dynamics can, in turn, influence antigenic diversity and recombination between genetically distinct parasites. Here, we embed a differential-equation model of parasite-immune system interactions within each of the individual humans represented in a discrete-event model of Plasmodium falciparum transmission, and examine the effects of human population turnover, parasite antigenic diversity, recombination, and gametocyte production on the dynamics of malaria. Our results indicate that the local persistence of P. falciparum increases with turnover in the human population and antigenic diversity in the parasite, particularly in combination, and that antigenic diversity arising from meiotic recombination in the parasite has complex differential effects on the persistence of founder and progeny genotypes. We also find that reductions in the duration of individual human infectivity to mosquitoes, even if universal, produce population-level effects only if near-absolute, and that, in competition, the persistence and prevalence of parasite genotypes with gametocyte production concordant with data exceed those of genotypes with higher gametocyte production. This new, integrated approach provides a framework for investigating relationships between pathogen dynamics within an individual host and pathogen dynamics within interacting host and vector populations.

  18. Particle dynamics modeling methods for colloid suspensions

    NASA Astrophysics Data System (ADS)

    Bolintineanu, Dan S.; Grest, Gary S.; Lechman, Jeremy B.; Pierce, Flint; Plimpton, Steven J.; Schunk, P. Randall

    2014-09-01

    We present a review and critique of several methods for the simulation of the dynamics of colloidal suspensions at the mesoscale. We focus particularly on simulation techniques for hydrodynamic interactions, including implicit solvents (Fast Lubrication Dynamics, an approximation to Stokesian Dynamics) and explicit/particle-based solvents (Multi-Particle Collision Dynamics and Dissipative Particle Dynamics). Several variants of each method are compared quantitatively for the canonical system of monodisperse hard spheres, with a particular focus on diffusion characteristics, as well as shear rheology and microstructure. In all cases, we attempt to match the relevant properties of a well-characterized solvent, which turns out to be challenging for the explicit solvent models. Reasonable quantitative agreement is observed among all methods, but overall the Fast Lubrication Dynamics technique shows the best accuracy and performance. We also devote significant discussion to the extension of these methods to more complex situations of interest in industrial applications, including models for non-Newtonian solvent rheology, non-spherical particles, drying and curing of solvent and flows in complex geometries. This work identifies research challenges and motivates future efforts to develop techniques for quantitative, predictive simulations of industrially relevant colloidal suspension processes.

  19. 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.

  20. Dynamic model for the popularity of websites.

    PubMed

    Lee, Chang-Yong; Kim, Seungwhan

    2002-03-01

    In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.

  1. Dynamic model for the popularity of websites

    NASA Astrophysics Data System (ADS)

    Lee, Chang-Yong; Kim, Seungwhan

    2002-03-01

    In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.

  2. BDI-modelling of complex intracellular dynamics.

    PubMed

    Jonker, C M; Snoep, J L; Treur, J; Westerhoff, H V; Wijngaards, W C A

    2008-03-07

    A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.

  3. ODE models for oncolytic virus dynamics

    PubMed Central

    Komarova, Natalia L.; Wodarz, Dominik

    2010-01-01

    Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remain uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the “fast spread” models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the “slow spread” models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers. PMID:20085772

  4. Dynamic causal modelling of distributed electromagnetic responses

    PubMed Central

    Daunizeau, Jean; Kiebel, Stefan J.; Friston, Karl J.

    2009-01-01

    In this note, we describe a variant of dynamic causal modelling for evoked responses as measured with electroencephalography or magnetoencephalography (EEG and MEG). We depart from equivalent current dipole formulations of DCM, and extend it to provide spatiotemporal source estimates that are spatially distributed. The spatial model is based upon neural-field equations that model neuronal activity on the cortical manifold. We approximate this description of electrocortical activity with a set of local standing-waves that are coupled though their temporal dynamics. The ensuing distributed DCM models source as a mixture of overlapping patches on the cortical mesh. Time-varying activity in this mixture, caused by activity in other sources and exogenous inputs, is propagated through appropriate lead-field or gain-matrices to generate observed sensor data. This spatial model has three key advantages. First, it is more appropriate than equivalent current dipole models, when real source activity is distributed locally within a cortical area. Second, the spatial degrees of freedom of the model can be specified and therefore optimised using model selection. Finally, the model is linear in the spatial parameters, which finesses model inversion. Here, we describe the distributed spatial model and present a comparative evaluation with conventional equivalent current dipole (ECD) models of auditory processing, as measured with EEG. PMID:19398015

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

    PubMed Central

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

    2007-01-01

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

  6. Quantitative Conformationally Sampled Pharmacophore (CSP) for δ Opioid Ligands: Reevaluation of hydrophobic moieties essential for biological activity

    PubMed Central

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

    2008-01-01

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

  7. Computational and dynamic models in neuroimaging

    PubMed Central

    Friston, Karl J.; Dolan, Raymond J.

    2010-01-01

    This article reviews the substantial impact computational neuroscience has had on neuroimaging over the past years. It builds on the distinction between models of the brain as a computational machine and computational models of neuronal dynamics per se; i.e., models of brain function and biophysics. Both sorts of model borrow heavily from computational neuroscience, and both have enriched the analysis of neuroimaging data and the type of questions we address. To illustrate the role of functional models in imaging neuroscience, we focus on optimal control and decision (game) theory; the models used here provide a mechanistic account of neuronal computations and the latent (mental) states represent by the brain. In terms of biophysical modelling, we focus on dynamic causal modelling, with a special emphasis on recent advances in neural-mass models for hemodynamic and electrophysiological time series. Each example emphasises the role of generative models, which embed our hypotheses or questions, and the importance of model comparison (i.e., hypothesis testing). We will refer to this theme, when trying to contextualise recent trends in relation to each other. PMID:20036335

  8. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

    PubMed

    Onorante, Luca; Raftery, Adrian E

    2016-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

  9. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

    PubMed Central

    Onorante, Luca; Raftery, Adrian E.

    2015-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

  10. 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

  11. 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.

  12. Pharmacophore alignment search tool: influence of scoring systems on text-based similarity searching.

    PubMed

    Hähnke, Volker; Schneider, Gisbert

    2011-06-01

    The text-based similarity searching method Pharmacophore Alignment Search Tool is grounded on pairwise comparisons of potential pharmacophoric points between a query and screening compounds. The underlying scoring matrix is of critical importance for successful virtual screening and hit retrieval from large compound libraries. Here, we compare three conceptually different computational methods for systematic deduction of scoring matrices: assignment-based, alignment-based, and stochastic optimization. All three methods resulted in optimized pharmacophore scoring matrices with significantly superior retrospective performance in comparison with simplistic scoring schemes. Computer-generated similarity matrices of pharmacophoric features turned out to agree well with a manually constructed matrix. We introduce the concept of position-specific scoring to text-based similarity searching so that knowledge about specific ligand-receptor binding patterns can be included and demonstrate its benefit for hit retrieval. The approach was also used for automated pharmacophore elucidation in agonists of peroxisome proliferator activated receptor gamma, successfully identifying key interactions for receptor activation.

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

    PubMed Central

    2012-01-01

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

  14. In Silico Design of Human IMPDH Inhibitors Using Pharmacophore Mapping and Molecular Docking Approaches

    PubMed Central

    Li, Rui-Juan; Wang, Ya-Li; Wang, Qing-He; Wang, Jian; Cheng, Mao-Sheng

    2015-01-01

    Inosine 5′-monophosphate dehydrogenase (IMPDH) is one of the crucial enzymes in the de novo biosynthesis of guanosine nucleotides. It has served as an attractive target in immunosuppressive, anticancer, antiviral, and antiparasitic therapeutic strategies. In this study, pharmacophore mapping and molecular docking approaches were employed to discover novel Homo sapiens IMPDH (hIMPDH) inhibitors. The Güner-Henry (GH) scoring method was used to evaluate the quality of generated pharmacophore hypotheses. One of the generated pharmacophore hypotheses was found to possess a GH score of 0.67. Ten potential compounds were selected from the ZINC database using a pharmacophore mapping approach and docked into the IMPDH active site. We find two hits (i.e., ZINC02090792 and ZINC00048033) that match well the optimal pharmacophore features used in this investigation, and it is found that they form interactions with key residues of IMPDH. We propose that these two hits are lead compounds for the development of novel hIMPDH inhibitors. PMID:25784957

  15. Virtual Lead Identification of Farnesyltransferase Inhibitors Based on Ligand and Structure-Based Pharmacophore Techniques

    PubMed Central

    Al-Balas, Qosay A.; Amawi, Haneen A.; Hassan, Mohammad A.; Qandil, Amjad M.; Almaaytah, Ammar M.; Mhaidat, Nizar M.

    2013-