Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach.

PubMed

Zeb, Amir; Park, Chanin; Son, Minky; Rampogu, Shailima; Alam, Syed Ibrar; Park, Seok Ju; Lee, Keun Woo

2018-06-01

Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value ([Formula: see text]), estimated Inhibitory Concentration (IC[Formula: see text]) ([Formula: see text]), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having goldfitness score [Formula: see text] and [Formula: see text], and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9[Formula: see text]Å), lowest potential energy ([Formula: see text][Formula: see text]kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.

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

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.

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

Virtual screening of cathepsin k inhibitors using docking and pharmacophore models.

PubMed

Ravikumar, Muttineni; Pavan, S; Bairy, Santhosh; Pramod, A B; Sumakanth, M; Kishore, Madala; Sumithra, Tirunagaram

2008-07-01

Cathepsin K is a lysosomal cysteine protease that is highly and selectively expressed in osteoclasts, the cells which degrade bone during the continuous cycle of bone degradation and formation. Inhibition of cathepsin K represents a potential therapeutic approach for diseases characterized by excessive bone resorption such as osteoporosis. In order to elucidate the essential structural features for cathepsin K, a three-dimensional pharmacophore hypotheses were built on the basis of a set of known cathepsin K inhibitors selected from the literature using catalyst program. Several methods are used in validation of pharmacophore hypothesis were presented, and the fourth hypothesis (Hypo4) was considered to be the best pharmacophore hypothesis which has a correlation coefficient of 0.944 with training set and has high prediction of activity for a set of 30 test molecules with correlation of 0.909. The model (Hypo4) was then employed as 3D search query to screen the Maybridge database containing 59,000 compounds, to discover novel and highly potent ligands. For analyzing intermolecular interactions between protein and ligand, all the molecules were docked using Glide software. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme inhibitor interaction pattern identified from molecular docking.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2.

PubMed

Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-07-01

Aldose reductase 2 (ALR2), which catalyzes the reduction of glucose to sorbitol using NADP as a cofactor, has been implicated in the etiology of secondary complications of diabetes. A pharmacophore model, Hypo1, was built based on 26 compounds with known ALR2-inhibiting activity values. Hypo1 contains important chemical features required for an ALR2 inhibitor, and demonstrates good predictive ability by having a high correlation coefficient (0.95) as well as the highest cost difference (128.44) and the lowest RMS deviation (1.02) among the ten pharmacophore models examined. Hypo1 was further validated by Fisher's randomization method (95%), test set (r = 0.91), and the decoy set shows the goodness of fit (0.70). Furthermore, during virtual screening, Hypo1 was used as a 3D query to screen the NCI database, and the hit leads were sorted by applying Lipinski's rule of five and ADME properties. The best-fitting leads were subjected to docking to identify a suitable orientation at the ALR2 active site. The molecule that showed the strongest interactions with the critical amino acids was used in molecular dynamics simulations to calculate its binding affinity to the candidate molecules. Thus, Hypo1 describes the key structure-activity relationship along with the estimated activities of ALR2 inhibitors. The hit molecules were searched against PubChem to find similar molecules with new scaffolds. Finally, four molecules were found to satisfy all of the chemical features and the geometric constraints of Hypo1, as well as to show good dock scores, PLPs and PMFs. Thus, we believe that Hypo1 facilitates the selection of novel scaffolds for ALR2, allowing new classes of ALR2 inhibitors to be designed.

Pharmacophore modeling of diverse classes of p38 MAP kinase inhibitors.

PubMed

Sarma, Rituparna; Sinha, Sharat; Ravikumar, Muttineni; Kishore Kumar, Madala; Mahmood, S K

2008-12-01

Mitogen-activated protein (MAP) p38 kinase is a serine-threonine protein kinase and its inhibitors are useful in the treatment of inflammatory diseases. Pharmacophore models were developed using HypoGen program of Catalyst with diverse classes of p38 MAP kinase inhibitors. The best pharmacophore hypothesis (Hypo1) with hydrogen-bond acceptor (HBA), hydrophobic (HY), hydrogen-bond donor (HBD), and ring aromatic (RA) as features has correlation coefficient of 0.959, root mean square deviation (RMSD) of 1.069 and configuration cost of 14.536. The model was validated using test set containing 119 compounds and had high correlation coefficient of 0.851. The results demonstrate that results obtained in this study can be considered to be useful and reliable tools in identifying structurally diverse compounds with desired biological activity.

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.

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.

Pharmacophore generation, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors.

PubMed

Tripathy, Swayansiddha; Azam, Mohammed Afzal; Jupudi, Srikanth; Sahu, Susanta Kumar

2017-10-11

FtsZ is an appealing target for the design of antimicrobial agent that can be used to defeat the multidrug-resistant bacterial pathogens. Pharmacophore modelling, molecular docking and molecular dynamics (MD) simulation studies were performed on a series of three-substituted benzamide derivatives. In the present study a five-featured pharmacophore model with one hydrogen bond acceptors, one hydrogen bond donors, one hydrophobic and two aromatic rings was developed using 97 molecules having MIC values ranging from .07 to 957 μM. A statistically significant 3D-QSAR model was obtained using this pharmacophore hypothesis with a good correlation coefficient (R 2  = .8319), cross validated coefficient (Q 2  = .6213) and a high Fisher ratio (F = 103.9) with three component PLS factor. A good correlation between experimental and predicted activity of the training (R 2  = .83) and test set (R 2  = .67) molecules were displayed by ADHRR.1682 model. The generated model was further validated by enrichment studies using the decoy test and MAE-based criteria to measure the efficiency of the model. The docking studies of all selected inhibitors in the active site of FtsZ protein showed crucial hydrogen bond interactions with Val 207, Asn 263, Leu 209, Gly 205 and Asn-299 residues. The binding free energies of these inhibitors were calculated by the molecular mechanics/generalized born surface area VSGB 2.0 method. Finally, a 15 ns MD simulation was done to confirm the stability of the 4DXD-ligand complex. On a wider scope, the prospect of present work provides insight in designing molecules with better selective FtsZ inhibitory potential.

Pharmacophore modeling, virtual screening and molecular docking of ATPase inhibitors of HSP70.

PubMed

Sangeetha, K; Sasikala, R P; Meena, K S

2017-10-01

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.

PubMed

Iqbal, Saleem; Anantha Krishnan, Dhanabalan; Gunasekaran, Krishnasamy

2017-12-13

Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease.

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.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

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. Copyright © 2015 Elsevier Inc. All rights reserved.

Pharmacophore-Based Similarity Scoring for DOCK

PubMed Central

2015-01-01

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

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. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

Simple idea to generate fragment and pharmacophore descriptors and their implications in chemical informatics.

PubMed

Catana, Cornel

2009-03-01

Using a well-defined set of fragments/pharmacophores, a new methodology to calculate fragment/ pharmacophore descriptors for any molecule onto which at least one fragment/pharmacophore can be mapped is presented. To each fragment/pharmacophore present in a molecule, we attach a descriptor that is calculated by identifying the molecule's atoms onto which it maps and summing over its constituent atomic descriptors. The attached descriptors are named C-fragment/pharmacophore descriptors, and this methodology can be applied to any descriptors defined at the atomic level, such as the partition coefficient, molar refractivity, electrotopological state, etc. By using this methodology, the same fragment/pharmacophore can be shown to have different values in different molecules resulting in better discrimination power. As we know, fragment and pharmacophore fingerprints have a lot of applications in chemical informatics. This study has attempted to find the impact of replacing the traditional value of "1" in a fingerprint with real numbers derived form C-fragment/pharmacophore descriptors. One way to do this is to assess the utility of C-fragment/ pharmacophore descriptors in modeling different end points. Here, we exemplify with data from CYP and hERG. The fact that, in many cases, the obtained models were fairly successful and C-fragment descriptors were ranked among the top ones supports the idea that they play an important role in correlation. When we modeled hERG with C-pharmacophore descriptors, however, the model performances decreased slightly, and we attribute this, mainly to the fact that there is no technique capable of handling multiple instances (states). We hope this will open new research, especially in the emerging field of machine learning. Further research is needed to see the impact of C-fragment/pharmacophore descriptors in similarity/dissimilarity applications.

Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design.

PubMed

Ebalunode, Jerry O; Zheng, Weifan; Tropsha, Alexander

2011-01-01

Optimization of chemical library composition affords more efficient identification of hits from biological screening experiments. The optimization could be achieved through rational selection of reagents used in combinatorial library synthesis. However, with a rapid advent of parallel synthesis methods and availability of millions of compounds synthesized by many vendors, it may be more efficient to design targeted libraries by means of virtual screening of commercial compound collections. This chapter reviews the application of advanced cheminformatics approaches such as quantitative structure-activity relationships (QSAR) and pharmacophore modeling (both ligand and structure based) for virtual screening. Both approaches rely on empirical SAR data to build models; thus, the emphasis is placed on achieving models of the highest rigor and external predictive power. We present several examples of successful applications of both approaches for virtual screening to illustrate their utility. We suggest that the expert use of both QSAR and pharmacophore models, either independently or in combination, enables users to achieve targeted libraries enriched with experimentally confirmed hit compounds.

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

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

PubMed Central

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

2015-01-01

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

Pharmer: efficient and exact pharmacophore search.

PubMed

Koes, David Ryan; Camacho, Carlos J

2011-06-27

Pharmacophore search is a key component of many drug discovery efforts. Pharmer is a new computational approach to pharmacophore search that scales with the breadth and complexity of the query, not the size of the compound library being screened. Two novel methods for organizing pharmacophore data, the Pharmer KDB-tree and Bloom fingerprints, enable Pharmer to perform an exact pharmacophore search of almost two million structures in less than a minute. In general, Pharmer is more than an order of magnitude faster than existing technologies. The complete source code is available under an open-source license at http://pharmer.sourceforge.net .

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.

Scaffold-based novel SHP2 allosteric inhibitors design using Receptor-Ligand pharmacophore model, virtual screening and molecular dynamics.

PubMed

Jin, Wen-Yan; Ma, Ying; Li, Wei-Ya; Li, Hong-Lian; Wang, Run-Ling

2018-04-01

SHP2 is a potential target for the development of novel therapies for SHP2-dependent cancers. In our research, with the aid of the 'Receptor-Ligand Pharmacophore' technique, a 3D-QSAR method was carried out to explore structure activity relationship of SHP2 allosteric inhibitors. Structure-based drug design was employed to optimize SHP099, an efficacious, potent, and selective SHP2 allosteric inhibitor. A novel class of selective SHP2 allosteric inhibitors was discovered by using the powerful 'SBP', 'ADMET' and 'CDOCKER' techniques. By means of molecular dynamics simulations, it was observed that these novel inhibitors not only had the same function as SHP099 did in inhibiting SHP2, but also had more favorable conformation for binding to the receptor. Thus, this report may provide a new method in discovering novel and selective SHP2 allosteric inhibitors. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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

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

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.

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening, docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH).

PubMed

Saxena, Shalini; Durgam, Laxman; Guruprasad, Lalitha

2018-05-14

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10 2 -1.3 × 10 6  nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.

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.

Targeting natural compounds against HER2 kinase domain as potential anticancer drugs applying pharmacophore based molecular modelling approaches.

PubMed

Rampogu, Shailima; Son, Minky; Baek, Ayoung; Park, Chanin; Rana, Rabia Mukthar; Zeb, Amir; Parameswaran, Saravanan; Lee, Keun Woo

2018-04-20

Human epidermal growth factor receptors are implicated in several types of cancers characterized by aberrant signal transduction. This family comprises of EGFR (ErbB1), HER2 (ErbB2, HER2/neu), HER3 (ErbB3), and HER4 (ErbB4). Amongst them, HER2 is associated with breast cancer and is one of the most valuable targets in addressing the breast cancer incidences. For the current investigation, we have performed 3D-QSAR based pharmacophore search for the identification of potential inhibitors against the kinase domain of HER2 protein. Correspondingly, a pharmacophore model, Hypo1, with four features was generated and was validated employing Fischer's randomization, test set method and the decoy test method. The validated pharmacophore was allowed to screen the colossal natural compounds database (UNPD). Subsequently, the identified 33 compounds were docked into the proteins active site along with the reference after subjecting them to ADMET and Lipinski's Rule of Five (RoF) employing the CDOCKER implemented on the Discovery Studio. The compounds that have displayed higher dock scores than the reference compound were scrutinized for interactions with the key residues and were escalated to MD simulations. Additionally, molecular dynamics simulations performed by GROMACS have rendered stable root mean square deviation values, radius of gyration and potential energy values. Eventually, based upon the molecular dock score, interactions between the ligands and the active site residues and the stable MD results, the number of Hits was culled to two identifying Hit1 and Hit2 has potential leads against HER2 breast cancers. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor

PubMed Central

Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R. PMID:29787591

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor.

PubMed

Khalid, Samra; Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R.

Synthesis, antimycobacterial evaluation and pharmacophore modeling of analogues of the natural product formononetin.

PubMed

Mutai, Peggoty; Pavadai, Elumalai; Wiid, Ian; Ngwane, Andile; Baker, Bienyameen; Chibale, Kelly

2015-06-15

The synthesis and antimycobacterial activity of formononetin analogues is hereby reported. Formononetin and its analogue 11E showed 88% and 95% growth inhibition, respectively, against the H37Rv strain of Mycobacterium tuberculosis. Pharmacophore modeling studies indicated that the presence of a hydroxyl group in formononetin and its analogues, is crucial for maintaining activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

2018-04-01

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.

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3.

PubMed

Kumar, B V S Suneel; Kotla, Rohith; Buddiga, Revanth; Roy, Jyoti; Singh, Sardar Shamshair; Gundla, Rambabu; Ravikumar, Muttineni; Sarma, Jagarlapudi A R P

2011-01-01

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149)and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM)and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.

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

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.

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.

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

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.

A 3D QSAR pharmacophore model and quantum chemical structure--activity analysis of chloroquine(CQ)-resistance reversal.

PubMed

Bhattacharjee, Apurba K; Kyle, Dennis E; Vennerstrom, Jonathan L; Milhous, Wilbur K

2002-01-01

Using CATALYST, a three-dimensional QSAR pharmacophore model for chloroquine(CQ)-resistance reversal was developed from a training set of 17 compounds. These included imipramine (1), desipramine (2), and 15 of their analogues (3-17), some of which fully reversed CQ-resistance, while others were without effect. The generated pharmacophore model indicates that two aromatic hydrophobic interaction sites on the tricyclic ring and a hydrogen bond acceptor (lipid) site at the side chain, preferably on a nitrogen atom, are necessary for potent activity. Stereoelectronic properties calculated by using AM1 semiempirical calculations were consistent with the model, particularly the electrostatic potential profiles characterized by a localized negative potential region by the side chain nitrogen atom and a large region covering the aromatic ring. The calculated data further revealed that aminoalkyl substitution at the N5-position of the heterocycle and a secondary or tertiary aliphatic aminoalkyl nitrogen atom with a two or three carbon bridge to the heteroaromatic nitrogen (N5) are required for potent "resistance reversal activity". Lowest energy conformers for 1-17 were determined and optimized to afford stereoelectronic properties such as molecular orbital energies, electrostatic potentials, atomic charges, proton affinities, octanol-water partition coefficients (log P), and structural parameters. For 1-17, fairly good correlation exists between resistance reversal activity and intrinsic basicity of the nitrogen atom at the tricyclic ring system, frontier orbital energies, and lipophilicity. Significantly, nine out of 11 of a group of structurally diverse CQ-resistance reversal agents mapped very well on the 3D QSAR pharmacophore model.

PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database.

PubMed

Wang, Xia; Shen, Yihang; Wang, Shiwei; Li, Shiliang; Zhang, Weilin; Liu, Xiaofeng; Lai, Luhua; Pei, Jianfeng; Li, Honglin

2017-07-03

The PharmMapper online tool is a web server for potential drug target identification by reversed pharmacophore matching the query compound against an in-house pharmacophore model database. The original version of PharmMapper includes more than 7000 target pharmacophores derived from complex crystal structures with corresponding protein target annotations. In this article, we present a new version of the PharmMapper web server, of which the backend pharmacophore database is six times larger than the earlier one, with a total of 23 236 proteins covering 16 159 druggable pharmacophore models and 51 431 ligandable pharmacophore models. The expanded target data cover 450 indications and 4800 molecular functions compared to 110 indications and 349 molecular functions in our last update. In addition, the new web server is united with the statistically meaningful ranking of the identified drug targets, which is achieved through the use of standard scores. It also features an improved user interface. The proposed web server is freely available at http://lilab.ecust.edu.cn/pharmmapper/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Binding Mode Analyses and Pharmacophore Model Development for Stilbene Derivatives as a Novel and Competitive Class of α-Glucosidase Inhibitors

PubMed Central

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

2014-01-01

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

Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads.

PubMed

Vadivelan, S; Sinha, B N; Rambabu, G; Boppana, Kiran; Jagarlapudi, Sarma A R P

2008-02-01

Histone deacetylase is one of the important targets in the treatment of solid tumors and hematological cancers. A total of 20 well-defined inhibitors were used to generate Pharmacophore models using and HypoGen module of Catalyst. These 20 molecules broadly represent 3 different chemotypes. The best HypoGen model consists of four-pharmacophore features--one hydrogen bond acceptor, one hydrophobic aliphatic and two ring aromatic centers. This model was validated against 378 known HDAC inhibitors with a correlation of 0.897 as well as enrichment factor of 2.68 against a maximum value of 3. This model was further used to retrieve molecules from NCI database with 238,819 molecules. A total of 4638 molecules from a pool of 238,819 molecules were identified as hits while 297 molecules were indicated as highly active. Also, a Similarity analysis has been carried out for set of 4638 hits with respect to most active molecule of each chemotypes which validated not only the Virtual Screening potential of the model but also identified the possible new Chemotypes. This type of Similarity analysis would prove to be efficient not only for lead generation but also for lead optimization.

A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA.

PubMed

Zhang, Tao; Wei, Dong-Qing; Chou, Kuo-Chen

2012-03-01

Comparative molecular field analysis (CoMFA) is a widely used 3D-QSAR method by which we can investigate the potential relation between biological activity of compounds and their structural features. In this study, a new application of this approach is presented by combining the molecular modeling with a new developed pharmacophore model specific to CYP1A2 active site. During constructing the model, we used the molecular dynamics simulation and molecular docking method to select the sensible binding conformations for 17 CYP1A2 substrates based on the experimental data. Subsequently, the results obtained via the alignment of binding conformations of substrates were projected onto the active- site residues, upon which a simple blueprint of active site was produced. It was validated by the experimental and computational results that the model did exhibit the high degree of rationality and provide useful insights into the substrate binding. It is anticipated that our approach can be extended to investigate the protein-ligand interactions for many other enzyme-catalyzed systems as well.

Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking.

PubMed

Wang, Yijun; Yang, Limei; Hou, Jiaying; Zou, Qing; Gao, Qi; Yao, Wenhui; Yao, Qizheng; Zhang, Ji

2018-02-12

The dual-target inhibitors tend to improve the response rate in treating tumors, comparing with the single-target inhibitors. Matrix metalloproteinase-2 (MMP-2) and histone deacetylase-6 (HDAC-6) are attractive targets for cancer therapy. In this study, the hierarchical virtual screening of dual MMP-2/HDAC-6 inhibitors from natural products is investigated. The pharmacophore model of MMP-2 inhibitors is built based on ligands, but the pharmacophore model of HDAC-6 inhibitors is built based on the experimental crystal structures of multiple receptor-ligand complexes. The reliability of these two pharmacophore models is validated subsequently. The hierarchical virtual screening, combining these two different pharmacophore models of MMP-2 and HDAC-6 inhibitors with molecular docking, is carried out to identify the dual MMP-2/HDAC-6 inhibitors from a database of natural products. The four potential dual MMP-2/HDAC-6 inhibitors of natural products, STOCK1 N-46177, STOCK1 N-52245, STOCK1 N-55477, and STOCK1 N-69706, are found. The studies of binding modes show that the screened four natural products can simultaneously well bind with the MMP-2 and HDAC-6 active sites by different kinds of interactions, to inhibit the MMP-2 and HDAC-6 activities. In addition, the ADMET properties of screened four natural products are assessed. These found dual MMP-2/HDAC-6 inhibitors of natural products could serve as the lead compounds for designing the new dual MMP-2/HDAC-6 inhibitors having higher biological activities by carrying out structural modifications and optimizations in the future studies.

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

PubMed

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 IC 50 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.

3D-QSAR pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B-NS3 protease inhibitors.

PubMed

Luo, Pei H; Zhang, Xuan R; Huang, Lan; Yuan, Lun; Zhou, Xang Z; Gao, X; Li, Ling S

2017-10-01

NS2B-NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer's model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC 50 values of ∼0.4637 µM and fitness of ∼57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B-NS3 protease.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents.

PubMed

Patel, Preeti; Singh, Avineesh; Patel, Vijay K; Jain, Deepak K; Veerasamy, Ravichandran; Rajak, Harish

2016-01-01

Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development. Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures. The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.

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

PubMed

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

2014-11-01

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

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

A review on PARP1 inhibitors: Pharmacophore modeling, virtual and biological screening studies to identify novel PARP1 inhibitors.

PubMed

Singh, Sardar Shamshair; Sarma, Jagarlapudi A R P; Narasu, Lakshmi; Dayam, Raveendra; Xu, Shili; Neamati, Nouri

2014-01-01

A tremendous research on Poly (ADP-ribose) polymerase (PARP) pertaining to cancer and ischemia is in very rapid progress. PARP's are a specific class of enzymes that repairs the damaged DNA. Recent findings suggest also that PARP-1 is the most abundantly expressed nuclear enzyme which involves in various therapeutic areas like inflammation, stroke, cardiac ischemia, cancer and diabetes. The current review describes the overview on clinical candidates of PARP1 and its current status in clinical trials. This paper also covers identification of potent PARP1 inhibitors using structure and ligand based pharmacophore models. Finally 36 potential hits were identified from the virtual screening of pharmacophore models and screened for PARP1 activity. 15 actives were identified as potent PARP1 inhibitors and further optimization of these analogues are in progress.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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} ofmore » 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.« less

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

PubMed

Kumar, Gyanendra; Kumaran, Desigan; Ahmed, S Ashraf; Swaminathan, Subramanyam

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(50) of 0.9 µM and a K(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. © 2012 International Union of Crystallography

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.

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2006-09-01

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

Ligand Based-Pharmacophore Modeling and Extended Bi oactivity Prediction for Salinosporamide A, B and C from Marine Actino mycetes Salinispora tropica.

PubMed

Dineshkumar, Kesavan; Vasudevan, Aparna; Hopper, Waheeta

2017-01-01

Actinomycetes produce structurally unique secondary metabolites with pharmaceutically essential bioactivities. Salinispora, an obligate marine actinomycete, produces structurally varied and unique secondary metabolites. There is plenty of scope for development of drugs from the novel compounds isolated from Salinispora. Anticancer, antibacterial and anti-protozoa activities have been shown for Salinosporamides A, B and C, the secondary metabolites identified from Salinispora, which make them interesting subjects for further extended biological activity prediction. An in silico ligand based-pharmacophore approach was used for the prediction of extended biological targets for salinosporamide A, B and C. Pharmacophore models of salinosporamide A, B and C were generated individually and screened against known drug databases. The drugs with best fitness score were shortlisted, and their respective targets pertaining to their bioactivity were retrieved. The predicted biological drug targets were docked with salinosporamide A, B and C for validation. The glucocorticoid receptor and methionine aminopeptidase 2 showed good docking score and binding energy with salinosporamide A, B and C. Molecular dynamics studies of the protein-ligand complexes showed stable interactions suggesting that the predicted new targets for salinosporamides might be promising. The glucocorticoid receptor and methionine aminopeptidase 2 could be possible new drug targets of bioactivity of salinosporamides. These proteins could be the druggable targets for antiinflammatory and anticancer activity of salinosporamides. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

[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.

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.

PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach

PubMed Central

Liu, Xiaofeng; Ouyang, Sisheng; Yu, Biao; Liu, Yabo; Huang, Kai; Gong, Jiayu; Zheng, Siyuan; Li, Zhihua; Li, Honglin; Jiang, Hualiang

2010-01-01

In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper. PMID:20430828

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

PubMed

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841

PRO_LIGAND: an approach to de novo molecular design. 2. Design of novel molecules from molecular field analysis (MFA) models and pharmacophores.

PubMed

Waszkowycz, B; Clark, D E; Frenkel, D; Li, J; Murray, C W; Robson, B; Westhead, D R

1994-11-11

A computational approach for molecular design, PRO_LIGAND, has been developed within the PROMETHEUS molecular design and simulation system in order to provide a unified framework for the de novo generation of diverse molecules which are either similar or complementary to a specified target. In this instance, the target is a pharmacophore derived from a series of active structures either by a novel interpretation of molecular field analysis data or by a pharmacophore-mapping procedure based on clique detection. After a brief introduction to PRO_LIGAND, a detailed description is given of the two pharmacophore generation procedures and their abilities are demonstrated by the elucidation of pharmacophores for steroid binding and ACE inhibition, respectively. As a further indication of its efficacy in aiding the rational drug design process, PRO_LIGAND is then employed to build novel organic molecules to satisfy the physicochemical constraints implied by the pharmacophores.

Enhancing the Sensitivity of Pharmacophore-Based Virtual Screening by Incorporating Customized ZBG Features: A Case Study Using Histone Deacetylase 8.

PubMed

Hou, Xuben; Du, Jintong; Liu, Renshuai; Zhou, Yi; Li, Minyong; Xu, Wenfang; Fang, Hao

2015-04-27

As key regulators of epigenetic regulation, human histone deacetylases (HDACs) have been identified as drug targets for the treatment of several cancers. The proper recognition of zinc-binding groups (ZBGs) will help improve the accuracy of virtual screening for novel HDAC inhibitors. Here, we developed a high-specificity ZBG-based pharmacophore model for HDAC8 inhibitors by incorporating customized ZBG features. Subsequently, pharmacophore-based virtual screening led to the discovery of three novel HDAC8 inhibitors with low micromole IC50 values (1.8-1.9 μM). Further studies demonstrated that compound H8-A5 was selective for HDAC8 over HDAC 1/4 and showed antiproliferation activity in MDA-MB-231 cancer cells. Molecular docking and molecular dynamic studies suggested a possible binding mode for H8-A5, which provides a good starting point for the development of HDAC8 inhibitors in cancer treatment.

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.

Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor

NASA Astrophysics Data System (ADS)

Prendergast, Kristine; Adams, Kym; Greenlee, William J.; Nachbar, Robert B.; Patchett, Arthur A.; Underwood, Dennis J.

1994-10-01

A systematic search has been used to derive a hypothesis for the receptor-bound conformation of A-II antagonists at the AT1 receptor. The validity of the pharmacophore hypothesis has been tested using CoMFA, which included 50 diverse A-II antagonists, spanning four orders of magnitude in activity. The resulting cross-validated R2 of 0.64 (conventional R2 of 0.76) is indicative of a good predictive model of activity, and has been used to estimate potency for a variety of non-peptidyl antagonists. The structural model for the non-peptide has been compared with respect to the natural substrate, A-II, by generating peptide to non-peptide overlays.

[The estimation method of compounds opiate activity based on universal three-dimensional model of the nonselective opiate pharmacophore].

PubMed

Kuz'mina, N E; Iashkir, V A; Merkulov, V A; Osipova, E S

2012-01-01

Created by means alternative strategy of structural similarity search universal three-dimensional model of the nonselective opiate pharmacophore and the estimation method of agonistic and antagonistic properties of opiate receptors ligands based on its were described. The examples of the present method use are given for opiate activity estimation of compounds essentially distinguished on the structure from opiates and traditional opioids.

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

Generation of ligand-based pharmacophore model and virtual screening for identification of novel tubulin inhibitors with potent anticancer activity.

PubMed

Chiang, Yi-Kun; Kuo, Ching-Chuan; Wu, Yu-Shan; Chen, Chung-Tong; Coumar, Mohane Selvaraj; Wu, Jian-Sung; Hsieh, Hsing-Pang; Chang, Chi-Yen; Jseng, Huan-Yi; Wu, Ming-Hsine; Leou, Jiun-Shyang; Song, Jen-Shin; Chang, Jang-Yang; Lyu, Ping-Chiang; Chao, Yu-Sheng; Wu, Su-Ying

2009-07-23

A pharmacophore model, Hypo1, was built on the basis of 21 training-set indole compounds with varying levels of antiproliferative activity. Hypo1 possessed important chemical features required for the inhibitors and demonstrated good predictive ability for biological activity, with high correlation coefficients of 0.96 and 0.89 for the training-set and test-set compounds, respectively. Further utilization of the Hypo1 pharmacophore model to screen chemical database in silico led to the identification of four compounds with antiproliferative activity. Among these four compounds, 43 showed potent antiproliferative activity against various cancer cell lines with the strongest inhibition on the proliferation of KB cells (IC(50) = 187 nM). Further biological characterization revealed that 43 effectively inhibited tubulin polymerization and significantly induced cell cycle arrest in G(2)-M phase. In addition, 43 also showed the in vivo-like anticancer effects. To our knowledge, 43 is the most potent antiproliferative compound with antitubulin activity discovered by computer-aided drug design. The chemical novelty of 43 and its anticancer activities make this compound worthy of further lead optimization.

Evaluation of the inhibitory effect of dihydropyridines on N-type calcium channel by virtual three-dimensional pharmacophore modeling.

PubMed

Ogihara, Takuo; Kano, Takashi; Kakinuma, Chihaya

2009-01-01

Currently, a new type of calcium channel blockers, which can inhibit not only L-type calcium channels abundantly expressed in vascular smooth muscles, but also N-type calcium channels that abound in the sympathetic nerve endings, have been developed. In this study, analysis on a like-for-like basis of the L- and N-type calcium channel-inhibitory activity of typical dihydropyridine-type calcium-channel blockers (DHPs) was performed. Moreover, to understand the differences of N-type calcium channel inhibition among DHPs, the binding of DHPs to the channel was investigated by means of hypothetical three-dimensional pharmacophore modeling using multiple calculated low-energy conformers of the DHPs. All of the tested compounds, i.e. cilnidipine (CAS 132203-70-4), efonidipine (CAS 111011-76-8), amlodipine (CAS 111470-99-6), benidipine (CAS 85387-35-5), azelnidipine (CAS 123524-52-7) and nifedipine (CAS 21829-25-4), potently inhibited the L-type calcium channel, whereas only cilnidipine inhibited the N-type calcium channel (IC50 value: 51.2 nM). A virtual three-dimensional structure of the N-type calcium channel was generated by using the structure of the peptide omega-conotoxin GVIA, a standard inhibitor of the channel, and cilnidipine was found to fit well into this pharmacophore model. Lipophilic potential maps of omega-conotoxin GVIA and cilnidipine supported this finding. Conformational overlay of cilnidipine and the other DHPs indicated that amlodipine and nifedipine were not compatible with the pharmacophore model because they did not contain an aromatic ring that was functionally equivalent to Tyr13 of omega-conotoxin GVIA. Azelnidipine, benidipine, and efonidipine, which have this type of aromatic ring, were not positively identified due to intrusions into the excluded volume. Estimation of virtual three-dimensional structures of proteins, such as ion channels, by using standard substrates and/or inhibitors may be a useful method to explore the mechanisms of

Discovery of novel InhA reductase inhibitors: application of pharmacophore- and shape-based screening approach.

PubMed

Kumar, Uday Chandra; Bvs, Suneel Kumar; Mahmood, Shaik; D, Sriram; Kumar-Sahu, Prashanta; Pulakanam, Sridevi; Ballell, Lluís; Alvarez-Gomez, Daniel; Malik, Siddharth; Jarp, Sarma

2013-03-01

InhA is a promising and attractive target in antimycobacterial drug development. InhA is involved in the reduction of long-chain trans-2-enoyl-ACP in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis. Recent studies have demonstrated that InhA is one of the targets for the second line antitubercular drug ethionamide. In the current study, we have generated quantitative pharmacophore models using known InhA inhibitors and validated using a large test set. The validated pharmacophore model was used as a query to screen an in-house database of 400,000 compounds and retrieved 25,000 hits. These hits were further ranked based on its shape and feature similarity with potent InhA inhibitor using rapid overlay of chemical structures (OpenEye™) and subsequent hits were subjected for docking. Based on the pharmacophore, rapid overlay of chemical structures model and docking interactions, 32 compounds with more than eight chemotypes were selected, purchased and assayed for InhA inhibitory activity. Out of the 32 compounds, 28 demonstrated 10-38% inhibition against InhA at 10 µM. Further optimization of these analogues is in progress and will update in due course.

Molecular Docking, Pharmacophore, and 3D-QSAR Approach: Can Adenine Derivatives Exhibit Significant Inhibitor Towards Ebola Virus?

PubMed Central

Rai, Amit; Aboumanei, Mohamed H.; Verma, Suraj P.; Kumar, Sachidanand; Raj, Vinit

2017-01-01

Introduction: Ebola Virus Disease (EVD) is caused by Ebola virus, which is often accompanied by fatal hemorrhagic fever upon infection in humans. This virus has caused the majority of deaths in human. There are no proper vaccinations and medications available for EVD. It is pivoting the attraction of scientist to develop the potent vaccination or novel lead to inhibit Ebola virus. Methods & Materials: In the present study, we developed 3D-QSAR and the pharmacophoric model from the previous reported potent compounds for the Ebola virus. Results & Discussion: Results & Discussion: The pharmacophoric model AAAP.116 was generated with better survival value and selectivity. Moreover, the 3D-QSAR model also showed the best r2 value 0.99 using PLS factor. Thereby, we found the higher F value, which demonstrated the statistical significance of both the models. Furthermore, homological modeling and molecular docking study were performed to analyze the affinity of the potent lead. This showed the best binding energy and bond formation with targeted protein. Conclusion: Finally, all the results of this study concluded that 3D-QSAR and Pharmacophore models may be helpful to search potent lead for EVD treatment in future. PMID:29387271

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.

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

PubMed

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

2015-01-01

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

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

Lead identification and optimization of novel collagenase inhibitors; pharmacophore and structure based studies

PubMed Central

Kalva, Sukesh; Vadivelan, S; Sanam, Ramadevi; Jagarlapudi, Sarma ARP; Saleena, Lilly M

2012-01-01

In this study, chemical feature based pharmacophore models of MMP-1, MMP-8 and MMP-13 inhibitors have been developed with the aid of HypoGen module within Catalyst program package. In MMP-1 and MMP-13, all the compounds in the training set mapped HBA and RA, while in MMP-8, the training set mapped HBA and HY. These features revealed responsibility for the high molecular bioactivity, and this is further used as a three dimensional query to screen the knowledge based designed molecules. These pharmacophore models for collagenases picked up some potent and novel inhibitors. Subsequently, docking studies were performed for the potent molecules and novel hits were suggested for further studies based on the docking score and active site interactions in MMP-1, MMP-8 and MMP-13. PMID:22553386

Pharmacophore modeling and in silico / in vitro screening for human cytochrome P450 11B1 & cytochrome P450 11B2 inhibitors

NASA Astrophysics Data System (ADS)

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-12-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing’s syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8-10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 µM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 µM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

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

PubMed

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

2013-10-28

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

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.

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

PubMed Central

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

2015-01-01

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

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

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors.

PubMed

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8 - 10 ), one selective CYP11B1 inhibitor (Compound 11 , IC 50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12 , IC 50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors

PubMed Central

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8–10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models. PMID:29312923

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

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

PubMed

Pirhadi, Somayeh; Ghasemi, Jahan B

2012-12-01

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity and low toxicity in antiretroviral combination therapies used to treat HIV. In this study, chemical feature based pharmacophore models of different classes of NNRT inhibitors of HIV-1 have been developed. The best HypoRefine pharmacophore model, Hypo 1, which has the best correlation coefficient (0.95) and the lowest RMS (0.97), contains two hydrogen bond acceptors, one hydrophobic and one ring aromatic feature, as well as four excluded volumes. Hypo 1 was further validated by test set and Fischer validation method. The best pharmacophore model was then utilized as a 3D search query to perform a virtual screening to retrieve potential inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies by Libdock and Gold methods to refine the retrieved hits. Finally, 7 top ranked compounds based on Gold score fitness function were subjected to in silico ADME studies to investigate for compliance with the standard ranges. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

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

Quantitative NTCP Pharmacophore and Lack of Association between DILI and NTCP Inhibition

PubMed Central

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

2014-01-01

The human sodium taurocholate cotransporting polypeptide (NTCP) is a hepatic bile acid transporter. Inhibition of NTCP uptake may potentially also prevent hepatitis B virus (HBV) infection. The first objective was to develop a quantitative pharmacophore for NTCP inhibition. Recent studies showed that hepatotoxic drugs could inhibit bile acid uptake into hepatocytes, without inhibiting canalicular efflux, and cause bile acid elevation in plasma. Hence, a second objective was to examine whether NTCP inhibition is associated with drug induced liver injury (DILI). Twenty-seven drugs from our previous study were used as the training set to develop a quantitative pharmacophore. From secondary screening from a drug database, six retrieved drugs and three drugs not retrieved by the model were tested for NTCP inhibition. Tertiary screening involved drugs known to cause DILI and not cause DILI. Overall, ninety-four drugs were assessed for hepatotoxicity and were assessed relative to NTCP inhibition. The quantitative pharmacophore possessed one hydrogen bond acceptor, one hydrogen bond donor, a hydrophobic feature, and excluded volumes. From 94 drugs, NTCP inhibitors and non-inhibitors were approximately equally distributed across the drugs of most DILI concern, less DILI concern, and no DILI concern, indicating no relationship between NTCP inhibition and DILI risk. Hence, an approach to treat HBV via NTCP inhibition is not expected to be associated with DILI. PMID:25220493

Quantitative NTCP pharmacophore and lack of association between DILI and NTCP Inhibition.

PubMed

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

2015-01-23

The human sodium taurocholate cotransporting polypeptide (NTCP) is a hepatic bile acid transporter. Inhibition of NTCP uptake may potentially also prevent hepatitis B virus (HBV) infection. The first objective was to develop a quantitative pharmacophore for NTCP inhibition. Recent studies showed that hepatotoxic drugs could inhibit bile acid uptake into hepatocytes, without inhibiting canalicular efflux, and cause bile acid elevation in plasma. Hence, a second objective was to examine whether NTCP inhibition is associated with drug induced liver injury (DILI). Twenty-seven drugs from our previous study were used as the training set to develop a quantitative pharmacophore. From secondary screening from a drug database, six retrieved drugs and three drugs not retrieved by the model were tested for NTCP inhibition. Tertiary screening involved drugs known to cause DILI and not cause DILI. Overall, ninety-four drugs were assessed for hepatotoxicity and were assessed relative to NTCP inhibition. The quantitative pharmacophore possessed one hydrogen bond acceptor, one hydrogen bond donor, a hydrophobic feature, and excluded volumes. From 94 drugs, NTCP inhibitors and non-inhibitors were approximately equally distributed across the drugs of most DILI concern, less DILI concern, and no DILI concern, indicating no relationship between NTCP inhibition and DILI risk. Hence, an approach to treat HBV via NTCP inhibition is not expected to be associated with DILI. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

2013-01-01

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Discovery Studio v3.1. Knowing the presence of the zinc feature is essential for inhibitor’s binding to the active site of FTase enzyme; further customization was applied to include this feature in the generated pharmacophore hypotheses. These pharmacophore hypotheses were thoroughly validated using various procedures such as ROC analysis and ligand pharmacophore mapping. The validated pharmacophore hypotheses were used to screen 3D databases to identify possible hits. Those which were both high ranked and showed sufficient ability to bind the zinc feature in active site, were further refined by applying drug-like criteria such as Lipiniski’s “rule of five” and ADMET filters. Finally, the two candidate compounds (ZINC39323901 and ZINC01034774) were allowed to dock using CDOCKER and GOLD in the active site of FTase enzyme to optimize hit selection. PMID:24276257

Virtual lead identification of farnesyltransferase inhibitors based on ligand and structure-based pharmacophore techniques.

PubMed

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

2013-05-27

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Discovery Studio v3.1. Knowing the presence of the zinc feature is essential for inhibitor's binding to the active site of FTase enzyme; further customization was applied to include this feature in the generated pharmacophore hypotheses. These pharmacophore hypotheses were thoroughly validated using various procedures such as ROC analysis and ligand pharmacophore mapping. The validated pharmacophore hypotheses were used to screen 3D databases to identify possible hits. Those which were both high ranked and showed sufficient ability to bind the zinc feature in active site, were further refined by applying drug-like criteria such as Lipiniski's "rule of five" and ADMET filters. Finally, the two candidate compounds (ZINC39323901 and ZINC01034774) were allowed to dock using CDOCKER and GOLD in the active site of FTase enzyme to optimize hit selection.

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

Pharmacophore mapping of arylbenzothiophene derivatives for MCF cell inhibition using classical and 3D space modeling approaches.

PubMed

Mukherjee, Subhendu; Nagar, Shuchi; Mullick, Sanchita; Mukherjee, Arup; Saha, Achintya

2008-01-01

Considering the worth of developing non-steroidal estrogen analogs, the present study explores the pharmacophore features of arylbenzothiophene derivatives for inhibitory activity to MCF-7 cells using classical QSAR and 3D space modeling approaches. The analysis shows that presence of phenolic hydroxyl group and ketonic linkage in the basic side chain of 2-arylbenzothiophene core of raloxifene derivatives are crucial. Additionally piperidine ring connected through ether linkage is favorable for inhibition of breast cancer cell line. These features for inhibitory activity are also highlighted through 3D space modeling approach that explored importance of critical inter features distance among HB-acceptor lipid, hydrophobic and HB-donor features in the arylbenzothiophene scaffold for activity.

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.

Iminopyrimidinones: A novel pharmacophore for the development of orally active renin inhibitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKittrick, Brian A.; Caldwell, John P.; Bara, Thomas

2015-04-01

The development of renin inhibitors with favorable oral pharmacokinetic profiles has been a longstanding challenge for the pharmaceutical industry. As part of our work to identify inhibitors of BACE1, we have previously developed iminopyrimidinones as a novel pharmacophore for aspartyl protease inhibition. In this letter we describe how we modified substitution around this pharmacophore to develop a potent, selective and orally active renin inhibitor.

Multicomplex-based pharmacophore-guided 3D-QSAR studies of N-substituted 2'-(aminoaryl)benzothiazoles as Aurora-A inhibitors.

PubMed

He, Gu; Qiu, Minghua; Li, Rui; Ouyang, Liang; Wu, Fengbo; Song, Xiangrong; Cheng, Li; Xiang, Mingli; Yu, Luoting

2012-06-01

Aurora-A has been known as one of the most important targets for cancer therapy, and some Aurora-A inhibitors have entered clinical trails. In this study, combination of the ligand-based and structure-based methods is used to clarify the essential quantitative structure-activity relationship of known Aurora-A inhibitors, and multicomplex-based pharmacophore-guided method has been suggested to generate a comprehensive pharmacophore of Aurora-A kinase based on a collection of crystal structures of Aurora-A-inhibitor complex. This model has been successfully used to identify the bioactive conformation and align 37 structurally diverse N-substituted 2'-(aminoaryl)benzothiazoles derivatives. The quantitative structure-activity relationship analyses have been performed on these Aurora-A inhibitors based on multicomplex-based pharmacophore-guided alignment. These results may provide important information for further design and virtual screening of novel Aurora-A inhibitors. © 2012 John Wiley & Sons A/S.

Pharmacophore Based Virtual Screening Approach to Identify Selective PDE4B Inhibitors

PubMed Central

Gaurav, Anand; Gautam, Vertika

2017-01-01

Phosphodiesterase 4 (PDE4) has been established as a promising target in asthma and chronic obstructive pulmonary disease. PDE4B subtype selective inhibitors are known to reduce the dose limiting adverse effect associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. To achieve this goal, ligand based pharmacophore modeling approach is employed. Separate pharmacophore hypotheses for PDE4B and PDE4D inhibitors were generated using HypoGen algorithm and 106 PDE4 inhibitors from literature having thiopyrano [3,2-d] Pyrimidines, 2-arylpyrimidines, and triazines skeleton. Suitable training and test sets were created using the molecules as per the guidelines available for HypoGen program. Training set was used for hypothesis development while test set was used for validation purpose. Fisher validation was also used to test the significance of the developed hypothesis. The validated pharmacophore hypotheses for PDE4B and PDE4D inhibitors were used in sequential virtual screening of zinc database of drug like molecules to identify selective PDE4B inhibitors. The hits were screened for their estimated activity and fit value. The top hit was subjected to docking into the active sites of PDE4B and PDE4D to confirm its selectivity for PDE4B. The hits are proposed to be evaluated further using in-vitro assays. PMID:29201082

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Y Cho; J Vermeire; J Merkel

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 inhibitionmore » 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.« less

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

PubMed

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

2005-01-01

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

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combined pharmacophore and structure-guided studies to identify diverse HSP90 inhibitors.

PubMed

Sanam, Ramadevi; Tajne, Sunita; Gundla, Rambabu; Vadivelan, S; Machiraju, Pavan Kumar; Dayam, Raveendra; Narasu, Lakshmi; Jagarlapudi, Sarma; Neamati, Nouri

2010-02-26

Heat Shock Protein 90 (HSP90), an ATP-dependent molecular chaperone, has emerged as a promising target in the treatment of cancer. Inhibition of HSP90 represents a new target of antitumor therapy, since it may influence many specific signaling pathways. Many HSP90 inhibitors bind to the ATP-binding pocket, inhibit chaperone function, resulting in cell death. Recent clinical trials for treatment of cancer have put HSP90's importance into focus and have highlighted the need for full scale research into HSP90 related pathways. Here we report five novel HSP90 inhibitors which were identified by using pharmacophore models and docking studies. We used highly discriminative pharmacophore model as a 3D query to search against database of approximately 1 M compounds and cluster analysis results yielded 455 compounds which were further subjected for docking. Glide docking studies suggested 122 compounds as in silico hits and these compounds were further selected for the cytotoxicity assay in the HSP90-over expressing SKBr3 cell line. Of the 122 compounds tested, 5 compounds inhibited cell growth with an IC(50) value less than 50 microM. Copyright 2009 Elsevier Inc. All rights reserved.

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

PubMed

Patel, Dhilon S; Bharatam, Prasad V

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Patel, Dhilon S.; Bharatam, Prasad V.

2006-01-01

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

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

PubMed

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

2011-02-01

Bifunctional ligands containing an ester linkage between morphine and the δ-selective pharmacophore Dmt-Tic were synthesized, and their binding affinity and functional bioactivity at the μ, δ and κ opioid receptors determined. Bifunctional ligands containing or not a spacer of β-alanine between the two pharmacophores lose the μ agonism deriving from morphine becoming partial μ agonists 4 or μ antagonists 5. Partial κ agonism is evidenced only for compound 4. Finally, both compounds showed potent δ antagonism. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Pharmacophore-based virtual screening, molecular docking, molecular dynamics simulation, and biological evaluation for the discovery of novel BRD4 inhibitors.

PubMed

Yan, Guoyi; Hou, Manzhou; Luo, Jiang; Pu, Chunlan; Hou, Xueyan; Lan, Suke; Li, Rui

2018-02-01

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore-based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC 50 values against human cancer cell lines MV4-11, A375, and HeLa were 4.2, 7.1, and 11.6 μm, respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound-healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5. © 2017 John Wiley & Sons A/S.

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.

Combination of Pharmacophore Matching, 2D Similarity Search, and In Vitro Biological Assays in the Selection of Potential 5-HT6 Antagonists from Large Commercial Repositories.

PubMed

Dobi, Krisztina; Flachner, Beáta; Pukáncsik, Mária; Máthé, Enikő; Bognár, Melinda; Szaszkó, Mária; Magyar, Csaba; Hajdú, István; Lőrincz, Zsolt; Simon, István; Fülöp, Ferenc; Cseh, Sándor; Dormán, György

2015-10-01

Rapid in silico selection of target-focused libraries from commercial repositories is an attractive and cost-effective approach. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compound databases, but the generated library requires further focusing. We report here a combination of the 2D approach with pharmacophore matching which was used for selecting 5-HT6 antagonists. In the first screening round, 12 compounds showed >85% antagonist efficacy of the 91 screened. For the second-round (hit validation) screening phase, pharmacophore models were built, applied, and compared with the routine 2D similarity search. Three pharmacophore models were created based on the structure of the reference compounds and the first-round hit compounds. The pharmacophore search resulted in a high hit rate (40%) and led to novel chemotypes, while 2D similarity search had slightly better hit rate (51%), but lacking the novelty. To demonstrate the power of the virtual screening cascade, ligand efficiency indices were also calculated and their steady improvement was confirmed. © 2015 John Wiley & Sons A/S.

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 (IC 50 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 Aβ 42 ) superior to phenserine (31% decrease of total Aβ) in SH-SY5Y-APP 695 cells at 50 µM. The dual actions of 43 on cholinergic and amyloidogenic pathways indicated potential uses as symptomatic and disease-modifying agents.

The desferrithiocin pharmacophore.

PubMed

Bergeron, R J; Liu, C Z; McManis, J S; Xia, M X; Algee, S E; Wiegand, J

1994-05-13

The (S)-desferrithiocin (DFT) skeleton is shown to be a useful pharmacophore on which to design orally effective iron chelators. While the study clearly indicates that formal reduction of the desazadesmethyldesferrithiocin thiazoline to a thiazolidine (6), expansion of the desmethyldesferrithiocin thiazoline to a thiazine (7), or substitution of the thiazoline sulfur of of desazedes-methyldesferrithiocin by an oxygen (8 and 9) lead to a substantial loss of activity, conversion of (S)-desmethyldesferrithiocin (1) to an N-methylhydroxamate (4) or to the hexacoordinate dihydroxamate ligand (5) results in active compounds. This investigation thus demonstrates which structural components of the siderophore are required for iron clearance after oral administration and suggests the use of the desferrithiocin platform as a vector for other chelators.

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.

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

PubMed

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

2013-08-01

Diisopropylfluorophosphate (DFP) is an organophosphorous insecticide used as a surrogate for the more toxic chemical warfare nerve agent sarin. DFP produces neurotoxicity in vivo and irreversibly decreases the area of population spikes recorded from the CA1 region of acute hippocampal slices. (1S,2E,4R,6R,7E,11E)-2,7,11-Cembratriene-4,6-diol (1) is a neuroprotective natural cembranoid that reverses DFP-induced damage both in vivo and in the hippocampal slice. Cembranoid 1 acts by noncompetitive inhibition of the α7 nicotinic acetylcholine receptor. This study aims at establishing a preliminary structure-activity relationship to define the neuroprotective cembranoid pharmacophores using the hippocampal slice assay and pharmacophore modeling. Fourteen natural, semisynthetic, or biocatalytic cembranoid analogues 2-15 related to 1 were tested for their capacity to protect the population spikes from DFP-induced damage and intrinsic toxicity. Twelve cembranoids caused significant reversal of DFP toxicity; only 3 active analogues displayed minor intrinsic toxicity at 10 μM. The C-4 epimer of 1 (2) and the 4-O-methyl ether analogue of 1 (3), were totally devoid of neuroprotective activity. The results suggested a model for cembranoid binding where the hydrophobic ring surface binds to a hydrophobic (Hbic) patch on the receptor molecule and an electronegative atom (oxygen or sulfur) in proper spatial relationship to the ring surface interacts with an electropositive group in the receptor binding site. A pharmacophore model consisting of 1 hydrogen bond acceptor (HBA), 2 Hbic, and 10 exclusion spheres was established using HipHop-REFINE and supported the above mentioned pharmacophoric hypothesis. Copyright © 2013 Elsevier Ltd. All rights reserved.

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

PubMed

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Exploring the Lead Compounds for Zika Virus NS2B-NS3 Protein: an e-Pharmacophore-Based Approach.

PubMed

Rohini, K; Agarwal, Pratika; Preethi, B; Shanthi, V; Ramanathan, K

2018-06-18

The rapid spread of the Zika virus and its association with the abnormal brain development constitute a global health emergency. With a continuing spread of the mosquito vector, the exposure is expected to accelerate in the coming years. Despite number of efforts, there is still no proper vaccine or medicine to combat this virus. Of note, the NS2B-NS3 protein is proven to be the potential target for the Zika virus therapeutics. Hence, e-pharmacophore-based drug design strategy was employed to identify potent inhibitors of NS2B-NS3 protein from ASINEX database consisting of 467,802 molecules. A 3D e-pharmacophore model was generated using PHASE module of Schrödinger Suite. The generated model consists of one hydrogen bond acceptor (A), two hydrogen bond donors (D), and two aromatic rings (R), ADDRR. The model was further evaluated for its ability to screen actives using enrichment analysis. Subsequently, high-throughput virtual screening protocol was employed, and the resultant hit molecules were also examined for its binding free energies and ADME properties using Prime MM-GBSA and Qikprop module of Schrodinger packages, respectively. Finally, the screened hit molecule was subjected to molecular dynamics simulation to examine its stability. Overall, the results from our analysis suggest that compound BAS 19192837 could be a potent inhibitor for the NS2B-NS3 protein of the Zika virus. It is also noteworthy to mention that our results are in good agreement with literature evidences. We hope that this result is of immense importance in designing potential drug molecules to combat the spread of Zika virus in the near future.

Pharmacophore-Based Repositioning of Approved Drugs as Novel Staphylococcus aureus NorA Efflux Pump Inhibitors.

PubMed

Astolfi, Andrea; Felicetti, Tommaso; Iraci, Nunzio; Manfroni, Giuseppe; Massari, Serena; Pietrella, Donatella; Tabarrini, Oriana; Kaatz, Glenn W; Barreca, Maria L; Sabatini, Stefano; Cecchetti, Violetta

2017-02-23

An intriguing opportunity to address antimicrobial resistance is represented by the inhibition of efflux pumps. Focusing on NorA, the most important efflux pump of Staphylococcus aureus, an efflux pump inhibitors (EPIs) library was used for ligand-based pharmacophore modeling studies. By exploitation of the obtained models, an in silico drug repositioning approach allowed for the identification of novel and potent NorA EPIs.

An integrated computational approach of molecular dynamics simulations, receptor binding studies and pharmacophore mapping analysis in search of potent inhibitors against tuberculosis.

PubMed

Agarwal, Shivangi; Verma, Ekta; Kumar, Vivek; Lall, Namrita; Sau, Samaresh; Iyer, Arun K; Kashaw, Sushil K

2018-05-03

Tuberculosis is an infectious chronic disease caused by obligate pathogen Mycobacterium tuberculosis that affects millions of people worldwide. Although many first and second line drugs are available for its treatment, but their irrational use has adversely lead to the emerging cases of multiple drug resistant and extensively drug-resistant tuberculosis. Therefore, there is an intense need to develop novel potent analogues for its treatment. This has prompted us to develop potent analogues against TB. The Mycobacterium tuberculosis genome provides us with number of validated targets to combat against TB. Study of Mtb genome disclosed six epoxide hydrolases (A to F) which convert harmful epoxide into diols and act as a potential drug target for rational drug design. Our current strategy is to develop such analogues which inhibits epoxide hydrolase enzyme present in Mtb genome. To achieve this, we adopted an integrated computational approach involving QSAR, pharmacophore mapping, molecular docking and molecular dynamics simulation studies. The approach envisaged vital information about the role of molecular descriptors, essential pharmacophoric features and binding energy for compounds to bind into the active site of epoxide hydrolase. Molecular docking analysis revealed that analogues exhibited significant binding to Mtb epoxide hydrolase. Further, three docked complexes 2s, 37s and 15s with high, moderate and low docking scores respectively were selected for molecular dynamics simulation studies. RMSD analysis revealed that all complexes are stable with average RMSD below 2 Å throughout the 10 ns simulations. The B-factor analysis showed that the active site residues of epoxide hydrolase are flexible enough to interact with inhibitor. Moreover, to confirm the binding of these urea derivatives, MM-GBSA binding energy analysis were performed. The calculations showed that 37s has more binding affinity (ΔGtotal = -52.24 kcal/mol) towards epoxide hydrolase

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

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

PubMed Central

Wang, Yen-Ling

2014-01-01

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

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

PubMed

Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

2016-09-15

Botulinum neurotoxins (BoNTs) are the most poisonous biological substance known to humans. They cause flaccid paralysis by blocking the release of acetylcholine at the neuromuscular junction. Here, we report a number of small molecule non-peptide inhibitors of BoNT serotype E. The structure-activity relationship and a pharmacophore model are presented. Although non-peptidic in nature, these inhibitors mimic key features of the uncleavable substrate peptide Arg-Ile-Met-Glu (RIME) of the SNAP-25 protein. Among the compounds tested, most of the potent inhibitors bear a zinc-chelating moiety connected to a hydrophobic and aromatic moiety through a carboxyl or amide linker. All of them show low micromolar IC50 values. Copyright © 2016 Elsevier Ltd. All rights reserved.

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 IC 50 values.« less

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.

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site.

PubMed

Massarotti, Alberto; Theeramunkong, Sewan; Mesenzani, Ornella; Caldarelli, Antonio; Genazzani, Armando A; Tron, Gian Cesare

2011-12-01

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile. © 2011 John Wiley & Sons A/S.

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

PubMed Central

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

2009-01-01

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

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

PubMed

Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding

2017-10-01

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.

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

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

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

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

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.

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

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.

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

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

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

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.

The interplay of descriptor-based computational analysis with pharmacophore modeling builds the basis for a novel classification scheme for feruloyl esterases.

PubMed

Udatha, D B R K Gupta; Kouskoumvekaki, Irene; Olsson, Lisbeth; Panagiotou, Gianni

2011-01-01

One of the most intriguing groups of enzymes, the feruloyl esterases (FAEs), is ubiquitous in both simple and complex organisms. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing high-added value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production and partial characterization of FAEs from fungi, while much less is known about FAEs of bacterial or plant origin. Initial classification studies on FAEs were restricted on sequence similarity and substrate specificity on just four model substrates and considered only a handful of FAEs belonging to the fungal kingdom. This study centers on the descriptor-based classification and structural analysis of experimentally verified and putative FAEs; nevertheless, the framework presented here is applicable to every poorly characterized enzyme family. 365 FAE-related sequences of fungal, bacterial and plantae origin were collected and they were clustered using Self Organizing Maps followed by k-means clustering into distinct groups based on amino acid composition and physico-chemical composition descriptors derived from the respective amino acid sequence. A Support Vector Machine model was subsequently constructed for the classification of new FAEs into the pre-assigned clusters. The model successfully recognized 98.2% of the training sequences and all the sequences of the blind test. The underlying functionality of the 12 proposed FAE families was validated against a combination of prediction tools and published experimental data. Another important aspect of the present work involves the development of pharmacophore models for the new FAE families, for which sufficient information on known substrates existed. Knowing the pharmacophoric features of a small molecule that are essential for binding to the

A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

PubMed

Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method.

PubMed

Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin

2018-01-01

The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Exploring protein-protein intermolecular recognition between meprin-α and endogenous protease regulator cystatinC coupled with pharmacophore elucidation.

PubMed

Chaudhuri, Ankur; Biswas, Sampa; Chakraborty, Sibani

2018-02-07

Meprins are a group of zinc metalloproteases of the astacin family which play a pivotal role in several physiological and pathologocal diseases. The inhibition of the meprins by various inhibitors, macromolecular and small molecules, is crucial in the control of several diseases. Human cystatinC, an amyloidogenic protein, is reported to be an endogenous inhibitor of meprin-α. In this computational study, we elucidate a rational model for meprinα-cystatinC complex using protein-protein docking. The complex model as well as the unbound form was evaluated by molecular dynamics simulation. A simulation study revealed higher stability of the complex owing to the presence of several interactions. Virtual alanine mutagenesis helps in identifying the hotspots on both proteins. Based on the frequency of occurrence of hotspot amino acids, it was possible to enumerate the important amino acids primarily responsible for protein stability present at the amino-terminal end of cystatin. Finally, pharmacophore elucidation carried out based on the information obtained from a series of small molecular inhibitors against meprin-α can be utilized in future for rational drug design and therapy.

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. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

PubMed

Steindl, Theodora M; Crump, Carolyn E; Hayden, Frederick G; Langer, Thierry

2005-10-06

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

Reactivity-based drug discovery using vitamin B(6)-derived pharmacophores.

PubMed

Wondrak, Georg T

2008-05-01

Endogenous reactive intermediates including photoexcited states of tissue chromophores, reactive oxygen species (ROS), reactive carbonyl species (RCS), transition metal ions, and Schiff bases have been implicated in the initiation and progression of diverse human pathologies including tumorigenesis, atherosclerosis, diabetes, and neurodegenerative disease. In contrast to structure-based approaches that target macromolecules by selective ligands, reactivity-based drug discovery uses chemical reagents as therapeutics that target reactive chemical species involved in human pathology. Reactivity-based design of prototype agents that effectively antagonize, modulate, and potentially even reverse the chemistry underlying tissue damage from oxidative and carbonyl stress therefore holds great promise in delivering significant therapeutic benefit. Apart from its established role as an essential cofactor for numerous enzymes, a large body of evidence suggests that B(6)-vitamers contain reactive pharmacophores that mediate therapeutically useful non-vitamin drug actions as potent antioxidants, metal chelators, carbonyl scavengers, Schiff base forming agents, and photosensitizers. Based on the fascinating chemical versatility of B(6)-derived pharmacophores, B(6)-vitamers are therefore promising lead compounds for reactivity-based drug design.

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.

Pharmacophore Refinement Guides the Design of Nanomolar-Range Botulinum Neurotoxin Serotype A Light Chain Inhibitors

PubMed Central

2010-01-01

Botulinum neurotoxins (BoNTs) are the deadliest of microbial toxins. The enzymes’ zinc(II) metalloprotease, referred to as the light chain (LC) component, inhibits acetylcholine release into neuromuscular junctions, resulting in the disease botulism. Currently, no therapies counter BoNT poisoning postneuronal intoxication; however, it is hypothesized that small molecules may be used to inhibit BoNT LC activity in the neuronal cytosol. Herein, we describe the pharmacophore-based design and chemical synthesis of potent [non-zinc(II) chelating] small molecule (nonpeptidic) inhibitors (SMNPIs) of the BoNT serotype A LC (the most toxic of the BoNT serotype LCs). Specifically, the three-dimensional superimpositions of 2-[4-(4-amidinephenoxy)phenyl]indole-6-amidine-based SMNPI regioisomers [Ki = 0.600 μM (±0.100 μM)], with a novel lead bis-[3-amide-5-(imidazolino)phenyl]terephthalamide (BAIPT)-based SMNPI [Ki = 8.52 μM (±0.53 μM)], resulted in a refined four-zone pharmacophore. The refined model guided the design of BAIPT-based SMNPIs possessing Ki values = 0.572 (±0.041 μM) and 0.900 μM (±0.078 μM). PMID:21116458

Discovery of potential ZAP-70 kinase inhibitors: pharmacophore design, database screening and docking studies.

PubMed

Sanam, Ramadevi; Vadivelan, S; Tajne, Sunita; Narasu, Lakshmi; Rambabu, G; Jagarlapudi, Sarma A R P

2009-12-01

The best ZAP-70 inhibitor model consists of four-pharmacophore features, (1) one hydrogen bond acceptor, (2) one hydrogen bond donor (3) one hydrophobic aliphatic and (4) one hydrophobic aromatic features. This model was validated against 110 known ZAP-70 inhibitors with a correlation of 0.902 as well as enrichment factor of 1.61 against a maximum value of 2. This model picked 4094 hits from a database of 238,819 molecules while 358 molecules were indicated as highly active. Subsequently, docking studies were performed on the hits and novel series of potent leads were suggested based on the interactions energy between ZAP-70 and the putative inhibitors which validated not only the virtual screening potential of the model but also identified the possible new Chemotypes.

Supercomputer applications in molecular modeling.

PubMed

Gund, T M

1988-01-01

An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.

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

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

PubMed Central

Geohagen, Brian C.; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence

2016-01-01

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

Allosteric ligands for the pharmacologically important Flavivirus target (NS5) from ZINC database based on pharmacophoric points, free energy calculations and dynamics correlation.

PubMed

Khan, Abbas; Saleem, Shoaib; Idrees, Muhammad; Ali, Syed Shujait; Junaid, Muhammad; Chandra Kaushik, Aman; Wei, Dong-Qing

2018-04-11

Dengue virus belongs to a group of human pathogens, which causes different diseases, dengue hemorrhagic fever and dengue shock syndrome in humans. It possesses RNA as a genetic material and is replicated with the aid of NS5 protein. RNA-dependent RNA polymerase (RdRp) is an important domain of NS5 in the replication of that virus. The catalytic process activity of RdRp is making it an important target for antiviral chemical therapy. To date, No FDA drug has been approved and marketed for the treatment of diseases caused by Dengue virus. So, there is a dire need to advance an area of active antiviral inhibitors that is safe, less expensive and widely available. An experimentally validated complex of Dengue NS5 and compound 27 (6LS) were used as pharmacophoric input and hits were identified. We also used Molecular dynamics (MD) simulations alongside free energy and dynamics of the internal residues of the apo and holo systems to understand the binding mechanism. Our analysis resulted that the three inhibitors (ZINC72070002, ZINC6551486, and ZINC39588257) greatly affected the interior dynamics and residual signaling to dysfunction the replicative role of NS5. The interaction of these inhibitors caused the loss of the correlated motion of NS5 near to the N terminus and helped the stability of the binding complex. This investigation provided a methodological route to discover allosteric inhibitors against the epidemics of this Flaviviruses. Allosteric inhibitors are important and major assets in considering the development of the competitive and robust antiviral agents such as against Dengue viral infection. Copyright © 2018 Elsevier Inc. All rights reserved.

Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors

NASA Astrophysics Data System (ADS)

Shahin, Rand; AlQtaishat, Saja; Taha, Mutasem O.

2012-02-01

Rho Kinase (ROCKII) has been recently implicated in several cardiovascular diseases prompting several attempts to discover and optimize new ROCKII inhibitors. Towards this end we explored the pharmacophoric space of 138 ROCKII inhibitors to identify high quality pharmacophores. The pharmacophoric models were subsequently allowed to compete within quantitative structure-activity relationship (QSAR) context. Genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing self-consistent QSAR of optimal predictive potential ( r 77 = 0.84, F = 18.18, r LOO 2 = 0.639, r PRESS 2 against 19 external test inhibitors = 0.494). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within ROCKII binding pocket. Receiver operating characteristic (ROC) curve analyses established the validity of QSAR-selected pharmacophores. Moreover, the successful pharmacophores models were found to be comparable with crystallographically resolved ROCKII binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds Eight submicromolar ROCKII inhibitors were identified. The most potent gave IC50 values of 0.7 and 1.0 μM.

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

PubMed

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

2011-03-15

Development of glutamate non-competitive antagonists of mGluR1 (Metabotropic glutamate receptor subtype 1) has increasingly attracted much attention in recent years due to their potential therapeutic application for various nervous disorders. Since there is no crystal structure reported for mGluR1, ligand-based virtual screening (VS) methods, typically pharmacophore-based VS (PB-VS), are often used for the discovery of mGluR1 antagonists. Nevertheless, PB-VS usually suffers a lower hit rate and enrichment factor. In this investigation, we established a multistep ligand-based VS approach that is based on a support vector machine (SVM) classification model and a pharmacophore model. Performance evaluation of these methods in virtual screening against a large independent test set, M-MDDR, show that the multistep VS approach significantly increases the hit rate and enrichment factor compared with the individual SB-VS and PB-VS methods. The multistep VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally a total of 20 compounds were selected from the top ranking compounds, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future. Copyright © 2011 Elsevier Ltd. All rights reserved.

Pharmacophore Hybridization To Discover Novel Topoisomerase II Poisons with Promising Antiproliferative Activity.

PubMed

Ortega, Jose Antonio; Riccardi, Laura; Minniti, Elirosa; Borgogno, Marco; Arencibia, Jose M; Greco, Maria L; Minarini, Anna; Sissi, Claudia; De Vivo, Marco

2018-02-08

We used a pharmacophore hybridization strategy to combine key structural elements of merbarone and etoposide and generated new type II topoisomerase (topoII) poisons. This first set of hybrid topoII poisons shows promising antiproliferative activity on human cancer cells, endorsing their further exploration for anticancer drug discovery.

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

PubMed

Jiang, Long; Li, Yu

2016-04-15

In this study, the properties of AhR binding affinity, bio-concentration factor, half-life and vapor pressure were selected as the typical indicators of biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential for polybrominated diphenyl ethers (PBDEs), respectively. A three-dimensional pharmacophore modeling assistant with a full factor experimental design for each property was used to reveal the significant pharmacophore features and the substituent effects to obtain reasonable modified schemes for the selected target PBDEs. Finally, the performances of the persistent organic pollutant (POP) properties, the synthesis feasibility and the fire resistance of the modified compounds were evaluated. The most influential pharmacophore feature for all POP properties was the hydrophobic group, especially the vinyl and propyl groups. Modified compounds with two additional hydrophobic groups exhibited a better regulatory performance. The average reduction in the proportions of the four POP properties for the modified compounds (except for 3-phenyl-BDE-15) was 70.60%, 52.44%, 47.04% and 70.88%. In addition, the energy and the C-Br bond dissociation enthalpy of the four typical PBDEs were higher than those of the modified compounds (except for 3-phenyl-BDE-15), indicating the synthesis feasibility and the lower energy barrier of the modified compounds to release Br free radicals to provide fire resistance. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-06-01

Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2',4',6'-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. Copyright © 2016 by The American Society for Pharmacology and

Minimal Pharmacophoric Elements and Fragment Hopping, an Approach Directed at Molecular Diversity and Isozyme Selectivity. Design of Selective Neuronal Nitric Oxide Synthase Inhibitors

PubMed Central

Ji, Haitao; Stanton, Benjamin Z.; Igarashi, Jotaro; Li, Huiying; Martásek, Pavel; Roman, Linda J.; Poulos, Thomas L.; Silverman, Richard B.

2010-01-01

Fragment hopping, a new fragment-based approach for de novo inhibitor design focusing on ligand diversity and isozyme selectivity, is described. The core of this approach is the derivation of the minimal pharmacophoric element for each pharmacophore. Sites for both ligand binding and isozyme selectivity are considered in deriving the minimal pharmacophoric elements. Five general-purpose libraries are established: the basic fragment library, the bioisostere library, the rules for metabolic stability, the toxicophore library, and the side chain library. These libraries are employed to generate focused fragment libraries to match the minimal pharmacophoric elements for each pharmacophore and then to link the fragment to the desired molecule. This method was successfully applied to neuronal nitric oxide synthase (nNOS), which is implicated in stroke and neurodegenerative diseases. Starting with the nitroarginine-containing dipeptide inhibitors we developed previously, a small organic molecule with a totally different chemical structure was designed, which showed nanomolar nNOS inhibitory potency and more than 1000-fold nNOS selectivity. The crystallographic analysis confirms that the small organic molecule with a constrained conformation can exactly mimic the mode of action of the dipeptide nNOS inhibitors. Therefore, a new peptidomimetic strategy, referred to as fragment hopping, which creates small organic molecules that mimic the biological function of peptides by a pharmacophore-driven strategy for fragment-based de novo design, has been established as a new type of fragment-based inhibitor design. As an open system, the newly established approach efficiently incorporates the concept of early “ADME/Tox” considerations and provides a basic platform for medicinal chemistry-driven efforts. PMID:18321097

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

PubMed

Modi, Palmi; Patel, Shivani; Chhabria, Mahesh T

2018-05-04

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1 H-NMR, 13 C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

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

PubMed

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

2015-01-01

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

EDULISS: a small-molecule database with data-mining and pharmacophore searching capabilities

PubMed Central

Hsin, Kun-Yi; Morgan, Hugh P.; Shave, Steven R.; Hinton, Andrew C.; Taylor, Paul; Walkinshaw, Malcolm D.

2011-01-01

We present the relational database EDULISS (EDinburgh University Ligand Selection System), which stores structural, physicochemical and pharmacophoric properties of small molecules. The database comprises a collection of over 4 million commercially available compounds from 28 different suppliers. A user-friendly web-based interface for EDULISS (available at http://eduliss.bch.ed.ac.uk/) has been established providing a number of data-mining possibilities. For each compound a single 3D conformer is stored along with over 1600 calculated descriptor values (molecular properties). A very efficient method for unique compound recognition, especially for a large scale database, is demonstrated by making use of small subgroups of the descriptors. Many of the shape and distance descriptors are held as pre-calculated bit strings permitting fast and efficient similarity and pharmacophore searches which can be used to identify families of related compounds for biological testing. Two ligand searching applications are given to demonstrate how EDULISS can be used to extract families of molecules with selected structural and biophysical features. PMID:21051336

Three-dimensional quantitative structure-activity relationship studies on UGT1A9-mediated 3-O-glucuronidation of natural flavonols using a pharmacophore-based comparative molecular field analysis model.

PubMed

Wu, Baojian; Morrow, John Kenneth; Singh, Rashim; Zhang, Shuxing; Hu, Ming

2011-02-01

Glucuronidation is often recognized as one of the rate-determining factors that limit the bioavailability of flavonols. Hence, design and synthesis of more bioavailable flavonols would benefit from the establishment of predictive models of glucuronidation using kinetic parameters [e.g., K(m), V(max), intrinsic clearance (CL(int)) = V(max)/K(m)] derived for flavonols. This article aims to construct position (3-OH)-specific comparative molecular field analysis (CoMFA) models to describe UDP-glucuronosyltransferase (UGT) 1A9-mediated glucuronidation of flavonols, which can be used to design poor UGT1A9 substrates. The kinetics of recombinant UGT1A9-mediated 3-O-glucuronidation of 30 flavonols was characterized, and kinetic parameters (K(m), V(max), CL(int)) were obtained. The observed K(m), V(max), and CL(int) values of 3-O-glucuronidation ranged from 0.04 to 0.68 μM, 0.04 to 12.95 nmol/mg/min, and 0.06 to 109.60 ml/mg/min, respectively. To model UGT1A9-mediated glucuronidation, 30 flavonols were split into the training (23 compounds) and test (7 compounds) sets. These flavonols were then aligned by mapping the flavonols to specific common feature pharmacophores, which were used to construct CoMFA models of V(max) and CL(int), respectively. The derived CoMFA models possessed good internal and external consistency and showed statistical significance and substantive predictive abilities (V(max) model: q(2) = 0.738, r(2) = 0.976, r(pred)(2) = 0.735; CL(int) model: q(2) = 0.561, r(2) = 0.938, r(pred)(2) = 0.630). The contour maps derived from CoMFA modeling clearly indicate structural characteristics associated with rapid or slow 3-O-glucuronidation. In conclusion, the approach of coupling CoMFA analysis with a pharmacophore-based structural alignment is viable for constructing a predictive model for regiospecific glucuronidation rates of flavonols by UGT1A9.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Discovery and Development of the Aryl O-Sulfamate Pharmacophore for Oncology and Women's Health.

PubMed

Thomas, Mark P; Potter, Barry V L

2015-10-08

In 1994, following work from this laboratory, it was reported that estrone-3-O-sulfamate irreversibly inhibits a new potential hormone-dependent cancer target steroid sulfatase (STS). Subsequent drug discovery projects were initiated to develop the core aryl O-sulfamate pharmacophore that, over some 20 years, have led to steroidal and nonsteroidal drugs in numerous preclinical and clinical trials, with promising results in oncology and women's health, including endometriosis. Drugs have been designed to inhibit STS, e.g., Irosustat, as innovative dual-targeting aromatase-steroid sulfatase inhibitors (DASIs) and as multitargeting agents for hormone-independent tumors, such as the steroidal STX140 and nonsteroidal counterparts, acting inter alia through microtubule disruption. The aryl sulfamate pharmacophore is highly versatile, operating via three distinct mechanisms of action, and imbues attractive pharmaceutical properties. This Perspective gives a personal view of the work leading both to the therapeutic concepts and these drugs, their current status, and how they might develop in the future.

Pharmacophore screening of the protein data bank for specific binding site chemistry.

PubMed

Campagna-Slater, Valérie; Arrowsmith, Andrew G; Zhao, Yong; Schapira, Matthieu

2010-03-22

A simple computational approach was developed to screen the Protein Data Bank (PDB) for putative pockets possessing a specific binding site chemistry and geometry. The method employs two commonly used 3D screening technologies, namely identification of cavities in protein structures and pharmacophore screening of chemical libraries. For each protein structure, a pocket finding algorithm is used to extract potential binding sites containing the correct types of residues, which are then stored in a large SDF-formatted virtual library; pharmacophore filters describing the desired binding site chemistry and geometry are then applied to screen this virtual library and identify pockets matching the specified structural chemistry. As an example, this approach was used to screen all human protein structures in the PDB and identify sites having chemistry similar to that of known methyl-lysine binding domains that recognize chromatin methylation marks. The selected genes include known readers of the histone code as well as novel binding pockets that may be involved in epigenetic signaling. Putative allosteric sites were identified on the structures of TP53BP1, L3MBTL3, CHEK1, KDM4A, and CREBBP.

Effect of lysine at C-terminus of the Dmt-Tic opioid pharmacophore.

PubMed

Balboni, Gianfranco; Onnis, Valentina; Congiu, Cenzo; Zotti, Margherita; Sasaki, Yusuke; Ambo, Akihiro; Bryant, Sharon D; Jinsmaa, Yunden; Lazarus, Lawrence H; Trapella, Claudio; Salvadori, Severo

2006-09-07

Substitution of Gly with side-chain-protected or unprotected Lys in lead compounds containing the opioid pharmacophore Dmt-Tic [H-Dmt-Tic-Gly-NH-CH(2)-Ph, mu agonist/delta antagonist; H-Dmt-Tic-Gly-NH-Ph, mu agonist/delta agonist; and H-Dmt-Tic-NH-CH(2)-Bid, delta agonist (Bid = 1H-benzimidazole-2-yl)] yielded a new series of compounds endowed with distinct pharmacological activities. Compounds (1-10) included high delta- (Ki(delta) = 0.068-0.64 nM) and mu-opioid affinities (Ki(mu) = 0.13-5.50 nM), with a bioactivity that ranged from mu-opioid agonism {10, H-Dmt-Tic-NH-CH[(CH2)4-NH2]-Bid (IC50 GPI = 39.7 nM)} to a selective mu-opioid antagonist [3, H-Dmt-Tic-Lys-NH-CH2-Ph (pA2(mu) = 7.96)] and a selective delta-opioid antagonist [5, H-Dmt-Tic-Lys(Ac)-NH-Ph (pA2(delta) = 12.0)]. The presence of a Lys linker provides new lead compounds in the formation of opioid peptidomimetics containing the Dmt-Tic pharmacophore with distinct agonist and/or antagonist properties.

Structure-based pharmacophore design and virtual screening for novel potential inhibitors of epidermal growth factor receptor as an approach to breast cancer chemotherapy.

PubMed

Mahernia, Shabnam; Hassanzadeh, Malihe; Sharifi, Niusha; Mehravi, Bita; Paytam, Fariba; Adib, Mehdi; Amanlou, Massoud

2018-02-01

Cancer cells are described with features of uncontrolled growth, invasion and metastasis. The epidermal growth factor receptor subfamily of tyrosine kinases (EGFR-TK) plays a crucial regulatory role in the control of cellular proliferation and progression of various cancers. Therefore, its inhibition might lead to the discovery of a new generation of anticancer drugs. In the present study, structure-based pharmacophore modeling, molecular docking and molecular dynamics simulations were applied to identify potential hits, which exhibited good inhibition on the proliferation of MCF-7 breast cancer cell line and favorable binding interactions on EGFR-TK. Selected compounds were examined for their anticancer activity against the Michigan Cancer Foundation-7 (MCF-7) breast cancer cell line which overexpresses EGFR using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium reduction assay. Compounds 1 and 2, with an isoindoline-1-one core, induced significant inhibition of breast cancer cells proliferation with IC[Formula: see text] values 327 and 370 nM, respectively.

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

PubMed

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

2016-07-01

A receptor-independent (RI) four-dimensional structure-activity relationship (4D-QSAR) formalism was applied to a set of sixty-four β-N-biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP-9). MMP-9 belongs to a group of enzymes related to the cleavage of several extracellular matrix components and has been associated to cancer invasiveness/metastasis. The best RI 4D-QSAR model was statistically significant (N=47; r(2) =0.91; q(2) =0.83; LSE=0.09; LOF=0.35; outliers=0). Leave-N-out (LNO) and y-randomization approaches indicated the QSAR model was robust and presented no chance correlation, respectively. Furthermore, it also had good external predictability (82 %) regarding the test set (N=17). In addition, the grid cell occupancy descriptors (GCOD) of the predicted bioactive conformation for the most potent inhibitor were successfully interpreted when docked into the MMP-9 active site. The 3D-pharmacophore findings were used to predict novel ligands and exploit the MMP-9 calculated binding affinity through molecular docking procedure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3β.

PubMed

Mishra, Pooja; Kesar, Seema; Paliwal, Sarvesh K; Chauhan, Monika; Madan, Kirtika

2018-05-29

Glycogen synthase kinase-3β plays a significant role in the regulation of various pathological pathways relating to central nervous system (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives a rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3β inhibitors. Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two hydrogen bond acceptors (HBA), one ring aromatic (RA), and one hydrophobe (HY), which were further affirmed by cost-function analysis, rm2 matrices, internal and external test set validation and Güner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3β Result: Four essential features, i.e., two hydrogen bond acceptors(HBA), one ring aromatic(RA), and one hydrophobe(HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

PubMed Central

2014-01-01

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

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

Discovery and Development of the Aryl O-Sulfamate Pharmacophore for Oncology and Women’s Health

PubMed Central

Thomas, Mark P.; Potter, Barry V. L.

2016-01-01

In 1994, following work from this laboratory, it was reported that estrone-3-O-sulfamate irreversibly inhibits a new potential hormone-dependent cancer target steroid sulfatase (STS). Subsequent drug discovery projects were initiated to develop the core aryl O-sulfamate pharmacophore that, over some twenty years, have led to steroidal and non-steroidal drugs in numerous pre-clinical and clinical trials, with promising results in oncology and women’s health, including endometriosis. Drugs have been designed to inhibit STS e.g. Irosustat, as innovative dual-targeting aromatase-steroid sulfatase inhibitors (DASIs) and as multi-targeting agents for hormone-independent tumors, such as the steroidal STX140 and non-steroidal counterparts, acting inter alia through microtubule disruption. The aryl sulfamate pharmacophore is highly versatile, operating via three distinct mechanisms of action and imbues attractive pharmaceutical properties. This Perspectives article gives a personal view of the work leading both to the therapeutic concepts and these drugs, their current status and how they might develop in the future. PMID:25992880

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe2435.39 is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na+ allosteric site in contrast to PAR2 agonist that showed Na+ relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands.

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease.

PubMed

Patel, Chirag N; Georrge, John J; Modi, Krunal M; Narechania, Moksha B; Patel, Daxesh P; Gonzalez, Frank J; Pandya, Himanshu A

2017-12-27

Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

Pharmacophore reassignment for induction of the immunosurveillance cytokine TRAIL.

PubMed

Jacob, Nicholas T; Lockner, Jonathan W; Kravchenko, Vladimir V; Janda, Kim D

2014-06-23

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is an immunosurveillance cytokine that kills cancer cells but demonstrates little toxicity against normal cells. While investigating the TRAIL-inducing imidazolinopyrimidinone TIC10, a misassignment of its active structure was uncovered. Syntheses of the two isomers, corresponding to the published and reassigned structures, are reported. The ability of each to induce TRAIL expression in macrophages was investigated and it was found that only the compound corresponding to the reassigned structure shows the originally reported activity; the compound corresponding to the published structure is inactive. Importantly, this structural reassignment has furnished a previously unknown antitumor pharmacophore. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2013-11-01

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

Common Pharmacophore of Structurally Distinct Small-Molecule Inhibitors of Intracellular Retrograde Trafficking of Ribosome Inactivating Proteins

NASA Astrophysics Data System (ADS)

Yu, Shichao; Park, Jewn Giew; Kahn, Jennifer Nielsen; Tumer, Nilgun E.; Pang, Yuan-Ping

2013-12-01

We reported previously (+/-)-2-(5-methylthiophen-2-yl)-3-phenyl-2,3-dihydroquinazolin-4(1H)-one [(+/-)-Retro-2cycl] as the chemical structure of Retro-2 that showed mouse protection against ricin, a notorious ribosome inactivating protein (RIP). Herein we report our chemical resolution of (+/-)-Retro-2cycl, analog synthesis, and cell-based evaluation showing that the two optically pure enantiomers and their achiral analog have nearly the same degree of cell protection against ricin as (+/-)-Retro-2cycl. We also report our computational studies explaining the lack of stereo preference and revealing a common pharmacophore of structurally distinct inhibitors of intracellular retrograde trafficking of RIPs. This pharmacophore comprises a central aromatic ring o-substituted by an aromatic ring and a moiety bearing an O or S atom attached to sp2 C atom(s). These results offer new insights into lead identification and optimization for RIP antidote development to minimize the global health threat caused by ribosome-inactivating proteins.

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

PubMed

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

2013-12-01

Inhibition of the enzyme acetylcholinesterase (AChE) has been shown to alleviate neurodegenerative diseases prompting several attempts to discover and optimize new AChE inhibitors. In this direction, we explored the pharmacophoric space of 85 AChE inhibitors to identify high quality pharmacophores. Subsequently, we implemented genetic algorithm-based quantitative structure-activity relationship (QSAR) modeling to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of explaining bioactivity variation among training compounds (r2(68)=0.94, F-statistic=125.8, r2 LOO=0.92, r2 PRESS against 17 external test inhibitors = 0.84). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within AChE binding pocket. The successful pharmacophores were comparable with crystallographically resolved AChE binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute list of compounds. Twenty-four low micromolar AChE inhibitors were identified. The most potent gave IC50 value of 1.0 μM.

Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5.

PubMed

Vijaya Prabhu, Sitrarasu; Singh, Sanjeev Kumar

2018-05-28

Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R 2  = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q 2  = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).

Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

PubMed

Lee, M L; Schneider, G

2001-01-01

Natural products were analyzed to determine whether they contain appealing novel scaffold architectures for potential use in combinatorial chemistry. Ring systems were extracted and clustered on the basis of structural similarity. Several such potential scaffolds for combinatorial chemistry were identified that are not present in current trade drugs. For one of these scaffolds a virtual combinatorial library was generated. Pharmacophoric properties of natural products, trade drugs, and the virtual combinatorial library were assessed using a self-organizing map. Obviously, current trade drugs and natural products have several topological pharmacophore patterns in common. These features can be systematically explored with selected combinatorial libraries based on a combination of natural product-derived and synthetic molecular building blocks.

Discovery of novel urokinase plasminogen activator (uPA) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis.

PubMed

Al-Sha'er, Mahmoud A; Khanfar, Mohammad A; Taha, Mutasem O

2014-01-01

Urokinase plasminogen activator (uPA)-a serine protease-is thought to play a central role in tumor metastasis and angiogenesis and, therefore, inhibition of this enzyme could be beneficial in treating cancer. Toward this end, we explored the pharmacophoric space of 202 uPA inhibitors using seven diverse sets of inhibitors to identify high-quality pharmacophores. Subsequently, we employed genetic algorithm-based quantitative structure-activity relationship (QSAR) analysis as a competition arena to select the best possible combination of pharmacophoric models and physicochemical descriptors that can explain bioactivity variation within the training inhibitors (r (2) 162 = 0.74, F-statistic = 64.30, r (2) LOO = 0.71, r (2) PRESS against 40 test inhibitors = 0.79). Three orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least three binding modes accessible to ligands within the uPA binding pocket. This conclusion was supported by receiver operating characteristic (ROC) curve analyses of the QSAR-selected pharmacophores. Moreover, the three pharmacophores were comparable with binding interactions seen in crystallographic structures of bound ligands within the uPA binding pocket. We employed the resulting pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds. The captured hits were tested in vitro. Overall, our modeling workflow identified new low micromolar anti-uPA hits.

Further studies on the effect of lysine at the C-terminus of the Dmt-Tic opioid pharmacophore.

PubMed

Balboni, Gianfranco; Onnis, Valentina; Congiu, Cenzo; Zotti, Margherita; Sasaki, Yusuke; Ambo, Akihiro; Bryant, Sharon D; Jinsmaa, Yunden; Lazarus, Lawrence H; Lazzari, Ilaria; Trapella, Claudio; Salvadori, Severo

2007-05-01

A wide range of activities are induced by Lys when introduced at C-terminus of the delta-opioid Dmt-Tic pharmacophore through the alpha-amine group, including: improved delta-antagonism, mu-agonism and mu-antagonism. Here we report the synthesis of a new series of compounds with the general formula H-Dmt-Tic-NH-(CH(2))(4)-CH(R)-R' (R=-NH(2), -NH-Ac, -NH-Z; R'=CO-NH-Ph, -CO-NH-CH(2)-Ph, -Bid) in which Lys is linked to Dmt-Tic through its side-chain amine group. All new compounds (1-9) displayed potent and selective delta-antagonism (MVD, pA(2)=7.81-8.27), which was independent of the functionalized alpha-amine and carboxylic groups of C-terminal Lys. This behaviour suggests a direct application as a prototype intermediate, such as Boc-Dmt-Tic-epsilon-Lys(Z)-OMe, which could be successfully applied in the synthesis (after Z or methyl ester removal) of unique designed multiple ligands containing the pharmacophore of the quintessential delta-antagonist Dmt-Tic and another opioid or biologically active non-opioid ligand.

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

Identification of the pharmacophore of the CC chemokine-binding proteins Evasin-1 and -4 using phage display.

PubMed

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

2014-11-14

To elucidate the ligand-binding surface of the CC chemokine-binding proteins Evasin-1 and Evasin-4, produced by the tick Rhipicephalus sanguineus, we sought to identify the key determinants responsible for their different chemokine selectivities by expressing Evasin mutants using phage display. We first designed alanine mutants based on the Evasin-1·CCL3 complex structure and an in silico model of Evasin-4 bound to CCL3. The mutants were displayed on M13 phage particles, and binding to chemokine was assessed by ELISA. Selected variants were then produced as purified proteins and characterized by surface plasmon resonance analysis and inhibition of chemotaxis. The method was validated by confirming the importance of Phe-14 and Trp-89 to the inhibitory properties of Evasin-1 and led to the identification of a third crucial residue, Asn-88. Two amino acids, Glu-16 and Tyr-19, were identified as key residues for binding and inhibition of Evasin-4. In a parallel approach, we identified one clone (Y28Q/N60D) that showed a clear reduction in binding to CCL3, CCL5, and CCL8. It therefore appears that Evasin-1 and -4 use different pharmacophores to bind CC chemokines, with the principal binding occurring through the C terminus of Evasin-1, but through the N-terminal region of Evasin-4. However, both proteins appear to target chemokine N termini, presumably because these domains are key to receptor signaling. The results also suggest that phage display may offer a useful approach for rapid investigation of the pharmacophores of small inhibitory binding proteins. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Application of 3D-QSAR, Pharmacophore, and Molecular Docking in the Molecular Design of Diarylpyrimidine Derivatives as HIV-1 Nonnucleoside Reverse Transcriptase Inhibitors.

PubMed

Liu, Genyan; Wang, Wenjie; Wan, Youlan; Ju, Xiulian; Gu, Shuangxi

2018-05-11

Diarylpyrimidines (DAPYs), acting as HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs), have been considered to be one of the most potent drug families in the fight against acquired immunodeficiency syndrome (AIDS). To better understand the structural requirements of HIV-1 NNRTIs, three-dimensional quantitative structure⁻activity relationship (3D-QSAR), pharmacophore, and molecular docking studies were performed on 52 DAPY analogues that were synthesized in our previous studies. The internal and external validation parameters indicated that the generated 3D-QSAR models, including comparative molecular field analysis (CoMFA, q 2 = 0.679, R 2 = 0.983, and r pred 2 = 0.884) and comparative molecular similarity indices analysis (CoMSIA, q 2 = 0.734, R 2 = 0.985, and r pred 2 = 0.891), exhibited good predictive abilities and significant statistical reliability. The docking results demonstrated that the phenyl ring at the C₄-position of the pyrimidine ring was better than the cycloalkanes for the activity, as the phenyl group was able to participate in π⁻π stacking interactions with the aromatic residues of the binding site, whereas the cycloalkanes were not. The pharmacophore model and 3D-QSAR contour maps provided significant insights into the key structural features of DAPYs that were responsible for the activity. On the basis of the obtained information, a series of novel DAPY analogues of HIV-1 NNRTIs with potentially higher predicted activity was designed. This work might provide useful information for guiding the rational design of potential HIV-1 NNRTI DAPYs.

Homology modeling, molecular dynamics and inhibitor binding study on MurD ligase of Mycobacterium tuberculosis.

PubMed

Arvind, Akanksha; Kumar, Vivek; Saravanan, Parameswaran; Mohan, C Gopi

2012-09-01

The cell wall of mycobacterium offers well validated targets which can be exploited for discovery of new lead compounds. MurC-MurF ligases catalyze a series of irreversible steps in the biosynthesis of peptidoglycan precursor, i.e. MurD catalyzes the ligation of D-glutamate to the nucleotide precursor UMA. The three dimensional structure of Mtb-MurD is not known and was predicted by us for the first time using comparative homology modeling technique. The accuracy and stability of the predicted Mtb-MurD structure was validated using Procheck and molecular dynamics simulation. Key interactions in Mtb-MurD were studied using docking analysis of available transition state inhibitors of E.coli-MurD. The docking analysis revealed that analogues of both L and D forms of glutamic acid have similar interaction profiles with Mtb-MurD. Further, residues His192, Arg382, Ser463, and Tyr470 are proposed to be important for inhibitor-(Mtb-MurD) interactions. We also identified few pharmacophoric features essential for Mtb-MurD ligase inhibitory activity and which can further been utilized for the discovery of putative antitubercular chemotherapy.

The Minimal Pharmacophore for Silent Agonism of the α7 Nicotinic Acetylcholine Receptor

PubMed Central

Chojnacka, Kinga; Horenstein, Nicole A.

2014-01-01

The minimum pharmacophore for activation of the human α7 nicotinic acetylcholine receptor (nAChR) is the tetramethylammonium cation. Previous work demonstrated that larger quaternary ammonium compounds, such as diethyldimethylammonium or 1-methyl quinuclidine, were α7-selective partial agonists, but additional increase in the size of the ammonium cation or the quinuclidine N-alkyl group by a single carbon to an N-ethyl group led to a loss of efficacy for ion channel activation. We report that although such compounds are ineffective at inducing the normal channel open state, they nonetheless regulate the induction of specific conformational states normally considered downstream of channel activation. We synthesized several panels of quaternary ammonium nAChR ligands that systematically varied the size of the substituents bonded to the central positively charged nitrogen atom. In these molecular series, we found a correlation between the molecular volume of the ligand and/or charge density, and the receptor’s preferred distribution among conformational states including the closed state, the active state, a nonconducting state that could be converted to an activated state by a positive allosteric modulator (PAM), and a PAM-insensitive nonconducting state. We hypothesize that the changes of molecular volume of an agonist’s cationic core subtly impact interactions at the subunit interface constituting the orthosteric binding site in such a way as to regulate the probability of conversions among the conformational states. We define a new minimal pharmacophore for the class of compounds we have termed “silent agonists,” which are able to induce allosteric modulator-dependent activation but not the normal activated state. PMID:24990939

Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure-activity relationship studies

NASA Astrophysics Data System (ADS)

de Souza, Anacleto S.; de Oliveira, Marcelo T.; Andricopulo, Adriano D.

2017-09-01

Chagas's is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. According to the World Health Organization, 7 million people are infected worldwide leading to 7000 deaths per year. Drugs available, nifurtimox and benzimidazole, are limited due to low efficacy and high toxicity. As a validated target, cruzain represents a major front in drug discovery attempts for Chagas disease. Herein, we describe the development of 2D QSAR (r_{{{pred}}}2 = 0.81) and a 3D-QSAR-based pharmacophore (r_{{{pred}}}2 = 0.82) from a series of non-covalent cruzain inhibitors represented mostly by oxadiazoles (lead compound, IC50 = 200 nM). Both models allowed us to map key intermolecular interactions in S1', S2 and S3 cruzain sub-sites (including halogen bond and C‒H/π). To probe the predictive capacity of obtained models, inhibitors available in the literature from different classes displaying a range of scaffolds were evaluate achieving mean absolute deviation of 0.33 and 0.51 for 2D and 3D models, respectively. CoMFA revealed an unexplored region where addition of bulky substituents to produce new compounds in the series could be beneficial to improve biological activity.

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

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.

Virtual screening and pharmacophore studies for ftase inhibitors using Indian plant anticancer compounds database.

PubMed

Khan, Abdul Hafeez; Prakash, Alok; Kumar, Dinesh; Rawat, Anil Kumar; Srivastava, Rajeev; Srivastava, Shipra

2010-07-06

Farnesyl transferase (FTase) is an enzyme responsible for post-translational modification in proteins having a carboxy-terminal CaaX motif in human. It catalyzes the attachment of a lipid group in proteins of RAS superfamily, which is essential in signal transduction. FTase has been recognized as an important target for anti cancer therapeutics. In this work, we performed virtual screening against FTase with entire 125 compounds from Indian Plant Anticancer Database using AutoDock 3.0.5 software. All compounds were docked within binding pocket containing Lys164, Tyr300, His248 and Tyr361 residues in crystal structure of FTase. These complexes were ranked according to their docking score, using methodology that was shown to achieve maximum accuracy. Finally we got three potent compounds with the best Autodock docking Score (Vinorelbine: -21.28 Kcal/mol, Vincristine: -21.74 Kcal/mol and Vinblastine: -22.14 Kcal/mol) and their energy scores were better than the FTase bound co-crystallized ligand (L- 739: -7.9 kcal/mol). These three compounds belong to Vinca alkaloids were analyzed through Python Molecular Viewer for their interaction studies. It predicted similar orientation and binding modes for these compounds with L-739 in FTase.Thus from the complex scoring and binding ability it is concluded that these Vinca alkaloids could be promising inhibitors for FTase. A 2-D pharmacophore was generated for these alkaloids using LigandScout to confirm it. A shared feature pharmacophore was also constructed that shows four common features (one hydogen bond Donar, Two hydrogen bond Acceptor and one ionizable area) help compounds to interact with this enzyme.

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

PubMed Central

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

2016-01-01

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

Efficient dynamic molecular simulation using QSAR model to know inhibition activity in breast cancer medicine

NASA Astrophysics Data System (ADS)

Zharifah, A.; Kusumowardani, E.; Saputro, A.; Sarwinda, D.

2017-07-01

According to data from GLOBOCAN (IARC) at 2012, breast cancer was the highest rated of new cancer case by 43.3 % (after controlled by age), with mortality rated as high as 12.9 %. Oncology is a major field which focusing on improving the development of drug and therapeutics cancer in pharmaceutical and biotechnology companies. Nowadays, many researchers lead to computational chemistry and bioinformatic for pharmacophore generation. A pharmacophore describes as a group of atoms in the molecule which is considered to be responsible for a pharmacological action. Prediction of biological function from chemical structure in silico modeling reduces the use of chemical reagents so the risk of environmental pollution decreased. In this research, we proposed QSAR model to analyze the composition of cancer drugs which assumed to be homogenous in character and treatment. Atomic interactions which analyzed are learned through parameters such as log p as descriptors hydrophobic, n_poinas descriptor contour strength and molecular structure, and also various concentrations inhibitor (micromolar and nanomolar) from NCBI drugs bank. The differences inhibitor activity was observed by the presence of IC 50 residues value from inhibitor substances at various concentration. Then, we got a general overview of the state of safety for drug stability seen from its IC 50 value. In our study, we also compared between micromolar and nanomolar inhibitor effect from QSAR model results. The QSAR model analysis shows that the drug concentration with nanomolar is better than micromolar, related with the content of inhibitor substances concentration. This QSAR model got the equation: Log 1/IC50 = (0.284) (±0.195) logP + (0.02) (±0.012) n_poin + (-0.005) (±0.083) Inhibition10.2nanoM + (0.1) (±0.079) Inhibition30.5nanoM + (-0.016) (±0.045) Inhibition91.5nanoM + (-2.572) (±1.570) (n = 13; r = 0.813; r2 = 0.660; s = 0.764; F = 2.720; q2 = 0.660).

Discovery of novel bacterial RNA polymerase inhibitors: pharmacophore-based virtual screening and hit optimization.

PubMed

Hinsberger, Stefan; Hüsecken, Kristina; Groh, Matthias; Negri, Matthias; Haupenthal, Jörg; Hartmann, Rolf W

2013-11-14

The bacterial RNA polymerase (RNAP) is a validated target for broad spectrum antibiotics. However, the efficiency of drugs is reduced by resistance. To discover novel RNAP inhibitors, a pharmacophore based on the alignment of described inhibitors was used for virtual screening. In an optimization process of hit compounds, novel derivatives with improved in vitro potency were discovered. Investigations concerning the molecular mechanism of RNAP inhibition reveal that they prevent the protein-protein interaction (PPI) between σ(70) and the RNAP core enzyme. Besides of reducing RNA formation, the inhibitors were shown to interfere with bacterial lipid biosynthesis. The compounds were active against Gram-positive pathogens and revealed significantly lower resistance frequencies compared to clinically used rifampicin.

Towards a Pharmacophore for Amyloid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Landau, Meytal; Sawaya, Michael R.; Faull, Kym F.

2011-09-16

compounds 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.« less

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

PubMed

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

2016-01-01

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

Comparative molecular field analysis to derive pharmacophore maps for induction doses of intravenous anaesthetic agents.

PubMed

Sear, J W

2011-03-01

The present study examines the molecular basis of induction of anaesthesia by i.v. hypnotic agents using comparative molecular field analysis (CoMFA). ED(50) induction doses for 14 i.v. anaesthetics in human subjects (expressed as molar dose per kilogram body weight) were obtained from the literature. Immobilizing potency data for the same 14 agents (expressed as the EC(50) plasma free drug concentrations that abolish movement in response to a noxious stimulus in 50% patients) were taken from our previous publication. These data were used to form CoMFA models for the two aspects of anaesthetic activity. Molecular alignment was achieved by field-fit minimization techniques. The lead structure for both models was eltanolone. The final CoMFA model for the ED(50) induction dose was based on two latent variables, and explained 99.3% of the variance in observed activities. It showed good intrinsic predictability (cross-validated q(2)=0.849). The equivalent model for immobilizing activity was also based on two latent variables, with r(2)=0.988 and q(2)=0.852. Although there was a correlation between -log ED(50) and -log EC(50) (r(2)=0.779), comparison of the pharmacophore maps showed poor correlation for both electrostatic and steric regions when isocontours were constructed by linking lattice grid points, making the greatest 40% contributions; the relative contributions of electrostatic and steric interactions differing between the models (induction dose: 2.5:1; immobilizing activity 1.8:1). Comparison of two CoMFA activity models shows only small elements of commonality, suggesting that different molecular features may be responsible for these two properties of i.v. anaesthetics.

Biosynthesis of antimycins with a reconstituted 3-formamidosalicylate pharmacophore in Escherichia coli.

PubMed

Liu, Joyce; Zhu, Xuejun; Seipke, Ryan F; Zhang, Wenjun

2015-05-15

Antimycins are a family of natural products generated from a hybrid nonribosomal peptide synthetase (NRPS)-polyketide synthase (PKS) assembly line. Although they possess an array of useful biological activities, their structural complexity makes chemical synthesis challenging, and their biosynthesis has thus far been dependent on slow-growing source organisms. Here, we reconstituted the biosynthesis of antimycins in Escherichia coli, a versatile host that is robust and easy to manipulate genetically. Along with Streptomyces genetic studies, the heterologous expression of different combinations of ant genes enabled us to systematically confirm the functions of the modification enzymes, AntHIJKL and AntO, in the biosynthesis of the 3-formamidosalicylate pharmacophore of antimycins. Our E. coli-based antimycin production system can not only be used to engineer the increased production of these bioactive compounds, but it also paves the way for the facile generation of novel and diverse antimycin analogues through combinatorial biosynthesis.

Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening

NASA Astrophysics Data System (ADS)

Yu, Miao; Gu, Qiong; Xu, Jun

2018-02-01

PI3Kα is a promising drug target for cancer chemotherapy. In this paper, we report a strategy of combing ligand-based and structure-based virtual screening to identify new PI3Kα inhibitors. First, naïve Bayesian (NB) learning models and a 3D-QSAR pharmacophore model were built based upon known PI3Kα inhibitors. Then, the SPECS library was screened by the best NB model. This resulted in virtual hits, which were validated by matching the structures against the pharmacophore models. The pharmacophore matched hits were then docked into PI3Kα crystal structures to form ligand-receptor complexes, which are further validated by the Glide-XP program to result in structural validated hits. The structural validated hits were examined by PI3Kα inhibitory assay. With this screening protocol, ten PI3Kα inhibitors with new scaffolds were discovered with IC50 values ranging 0.44-31.25 μM. The binding affinities for the most active compounds 33 and 74 were estimated through molecular dynamics simulations and MM-PBSA analyses.

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.

Database on pharmacophore analysis of active principles, from medicinal plants

PubMed Central

Pitchai, Daisy; Manikkam, Rajalakshmi; Rajendran, Sasikala R; Pitchai, Gnanamani

2010-01-01

Plants continue to be a major source of medicines, as they have been throughout human history. In the present days, drug discovery from plants involves a multidisciplinary approach combining ethnobotanical, phytochemical and biological techniques to provide us new chemical compounds (lead molecules) for the development of drugs against various pharmacological targets, including cancer, diabetes and its secondary complications. In view of this need in current drug discovery from medicinal plants, here we describe another web database containing the information of pharmacophore analysis of active principles possessing antidiabetic, antimicrobial, anticancerous and antioxidant properties from medicinal plants. The database provides the botanical, taxonomic classification, biochemical as well as pharmacological properties of medicinal plants. Data on antidiabetic, antimicrobial, anti oxidative, anti tumor and anti inflammatory compounds, and their physicochemical properties, SMILES Notation, Lipinski's properties are included in our database. One of the proposed features in the database is the predicted ADMET values and the interaction of bioactive compounds to the target protein. The database alphabetically lists the compound name and also provides tabs separating for anti microbial, antitumor, antidiabetic, and antioxidative compounds. Availability http://www.hccbif.info / PMID:21346859

Delta-opiate DPDPE in magnetically oriented phospholipid micelles: binding and arrangement of aromatic pharmacophores.

PubMed Central

Rinaldi, F; Lin, M; Shapiro, M J; Petersheim, M

1997-01-01

D-Penicillamine(2,5)-enkephalin (DPDPE) is a potent opioid peptide that exhibits a high selectivity for the delta-opiate receptors. This zwitterionic peptide has been shown, by pulsed-field gradient 1H NMR diffusion studies, to have significant affinity for a zwitterionic phospholipid bilayer. The bilayer lipid is in the form of micelles composed of dihexanoylphosphatidylcholine (DHPC) and dimyristoylphosphatidylcholine (DMPC) mixtures, where the DMPC forms the bilayer structure. At high lipid concentration (25% w/w) these micelles orient in the magnetic field of an NMR spectrometer. The resulting 1H-13C dipolar couplings and chemical shift changes in the natural abundance 13C resonances for the Tyr and Phe aromatic rings were used to characterize the orientations in the bilayer micelles of these two key pharmacophores. Images FIGURE 1 FIGURE 8 PMID:9414244

Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2016-04-01

Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

PubMed

Mishra, Vinita; Pathak, Chandramani

2018-05-29

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

Pharmacophoric characteristics of dengue virus NS2B/NS3pro inhibitors: a systematic review of the most promising compounds.

PubMed

Leonel, Camyla Alves; Lima, William Gustavo; Dos Santos, Michelli; Ferraz, Ariane Coelho; Taranto, Alex Gutterres; de Magalhães, José Carlos; Dos Santos, Luciana Lara; Ferreira, Jaqueline Maria Siqueira

2018-03-01

Dengue virus (DENV) infection can lead to a wide range of clinical manifestations, including fatal hemorrhagic complications. There is a need to find effective pharmacotherapies to treat this disease due to the lack of specific immunotherapies and antiviral drugs. That said, the DENV NS2B/NS3pro protease complex is essential in both the viral multiplication cycle and in disease pathogenesis, and is considered a promising target for new antiviral therapies. Here, we performed a systematic review to evaluate the pharmacophoric characteristics of promising compounds against NS2B/NS3pro reported in the past 10 years. Online searches in the PUBMED/MEDLINE and SCOPUS databases resulted in 165 articles. Eight studies, which evaluated 3,384,268 molecules exhibiting protease inhibition activity, were included in this review. These studies evaluated anti-dengue activity in vitro and the IC 50 and EC 50 values were provided. Most compounds exhibited non-competitive inhibition. Cytotoxicity was evaluated in BHK-21, Vero, and LLC-MK2 cells, and the CC 50 values obtained ranged from < 1.0 to 780.5 µM. Several groups were associated with biological activity against dengue, including nitro, catechol, halogen and ammonium quaternaries. Thus, these groups seem to be potential pharmacophores that can be further investigated to treat dengue infections.

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

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

Relationship between structure and P-glycoprotein inhibitory activity of dimeric peptides related to the Dmt-Tic pharmacophore.

PubMed

Ambo, Akihiro; Ohkatsu, Hiromichi; Minamizawa, Motoko; Watanabe, Hideko; Sugawara, Shigeki; Nitta, Kazuo; Tsuda, Yuko; Okada, Yoshio; Sasaki, Yusuke

2012-03-15

To develop novel inhibitors of P-glycoprotein (P-gp), dimeric peptides related to an opioid peptide containing the Dmt-Tic pharmacophore were synthesized and their P-gp inhibitory activities were analyzed. Of the 30 analogs synthesized, N(α),N(ε)-[(CH(3))(2)Mle-Tic](2)Lys-NH(2) and its D-Lys analog were found to exhibit potent P-gp inhibitory activity, twice that of verapamil, in doxorubicin-resistant K562 cells. Structure-activity studies indicated that the correct hydrophobicity and spacer length between two aromatic rings are important structural elements in this series of analogs for inhibition of P-gp. Copyright © 2012 Elsevier Ltd. All rights reserved.

Toward the definition of stereochemical requirements for MT2-selective antagonists and partial agonists by studying 4-phenyl-2-propionamidotetralin derivatives.

PubMed

Bedini, Annalida; Lucarini, Simone; Spadoni, Gilberto; Tarzia, Giorgio; Scaglione, Francesco; Dugnani, Silvana; Pannacci, Marilou; Lucini, Valeria; Carmi, Caterina; Pala, Daniele; Rivara, Silvia; Mor, Marco

2011-12-22

New derivatives of 4-phenyl-2-propionamidotetralin (4-P-PDOT) were prepared and tested on cloned MT1 and MT2 receptors, with the purpose of merging previously reported pharmacophores for nonselective agonists and for MT2-selective antagonists. A 8-methoxy group increases binding affinity of both (±)-cis- and (±)-trans-4-P-PDOT, and it can be bioisosterically replaced by a bromine. Conformational analysis of 8-methoxy-4-P-PDOT by molecular dynamics, supported by NMR data, revealed an energetically favored conformation for the (2S,4S)-cis isomer and a less favorable conformation for the (2R,4S)-trans one, fulfilling the requirements of a pharmacophore model for nonselective melatonin receptor agonists. A new superposition model, including features characteristic of MT2-selective antagonists, suggests that MT1/MT2 agonists and MT2 antagonists can share the same arrangement for their pharmacophoric elements. The model correctly predicted the eutomers of (±)-cis- and (±)-trans-4-P-PDOT. The model was validated by preparing three dihydronaphthalene derivatives, either able or not able to reproduce the putative active conformation of 4-P-PDOT.

Identification of novel inhibitors of human Chk1 using pharmacophore-based virtual screening and their evaluation as potential anti-cancer agents

NASA Astrophysics Data System (ADS)

Kumar, Vikash; Khan, Saman; Gupta, Priyanka; Rastogi, Namrata; Mishra, Durga Prasad; Ahmed, Shakil; Siddiqi, Mohammad Imran

2014-12-01

Kinases are one of the major players in cancer development and progression. Serine threonine kinases such as human checkpoint kinase-1 (Chk1), Mek1 and cyclin-dependent kinases have been identified as promising targets for cancer treatment. Chk1 is an important kinase with vital role in cell cycle arrest and many potent inhibitors targeted to Chk1 have been reported and few are currently in clinical trials. Considering the emerging importance of Chk1 inhibitors in cancer treatment there is a need to widen the chemical space of Chk1 inhibitors. In this study, we are reporting an integrated in silico approach to identify novel competitive Chk1 inhibitors. A 4-features pharmacophore model was derived from a co-crystallized structure of known potent Chk1 inhibitor and subjected to screen Maybridge compound library. Hits obtained from the screening were docked into the Chk1 active site and filtered on the basis of docking score and the number of pharmacophoric features showing conserved interaction within the active site of Chk1. Further, five compounds from the top ranking hits were subjected to in vitro evaluation as Chk1 inhibitor. After the kinase assay, four compounds were found to be active against human Chk1 (IC50 range from 4.2 to 12.5 µM). Subsequent study using the cdc25-22 mutant yeast cells revealed that one of compound (SPB07479; IC50 = 4.24 µM) promoted the formation of multinucleated cells, therefore overriding the cell cycle checkpoint. Validation studies using normal and human cancer cell lines, indicated that SPB07479 significantly inhibited proliferation of cervical cancer cells as a single agent and chemosensitized glioma and pancreatic cancer cell lines to standard chemotherapy while sparing normal cells. Additionally SPB07479 did not show significant cytotoxicity in normal cells. In conclusion we report that SPB07479 appear promising for further development of Chk1 inhibitors. This study also highlights the role of conserved water molecules in

Dynamical Galam model

NASA Astrophysics Data System (ADS)

Cheon, Taksu; Galam, Serge

2018-06-01

We introduce a model of temporal evolution of political opinions which amounts to a dynamical extension of Galam model in which the proportions of inflexibles are treated as dynamical variables. We find that the critical value of inflexibles in the original Galam model now turns into a fixed point of the system whose stability controls the phase trajectory of the political opinions. The appearance of two phases is found, in which majority-preserving and regime-changing limit cycles are respectively dominant, and the phase transition between them is observed.

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study.

PubMed

Hassan, Mubashir; Abbas, Qamar; Ashraf, Zaman; Moustafa, Ahmed A; Seo, Sung-Yum

2017-06-01

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (-11.70, -12.1, -9.90 and -11.20kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds

New insights into the stereochemical requirements of the bradykinin B2 receptor antagonists binding

NASA Astrophysics Data System (ADS)

Lupala, Cecylia S.; Gomez-Gutierrez, Patricia; Perez, Juan J.

2016-01-01

Bradykinin (BK) is a member of the kinin family, released in response to inflammation, trauma, burns, shock, allergy and some cardiovascular diseases, provoking vasodilatation and increased vascular permeability among other effects. Their actions are mediated through at least two G-protein coupled receptors, B1 a receptor up-regulated during inflammation episodes or tissue trauma and B2 that is constitutively expressed in a variety of cell types. The goal of the present work is to carry out a structure-activity study of BK B2 antagonism, taking into account the stereochemical features of diverse non-peptide antagonists and the way these features translate into ligand anchoring points to complementary regions of the receptor, through the analysis of the respective ligand-receptor complex. For this purpose an atomistic model of the BK B2 receptor was built by homology modeling and subsequently refined embedded in a lipid bilayer by means of a 600 ns molecular dynamics trajectory. The average structure from the last hundred nanoseconds of the molecular dynamics trajectory was energy minimized and used as model of the receptor for docking studies. For this purpose, a set of compounds with antagonistic profile, covering maximal diversity were selected from the literature. Specifically, the set of compounds include Fasitibant, FR173657, Anatibant, WIN64338, Bradyzide, CHEMBL442294, and JSM10292. Molecules were docked into the BK B2 receptor model and the corresponding complexes analyzed to understand ligand-receptor interactions. The outcome of this study is summarized in a 3D pharmacophore that explains the observed structure-activity results and provides insight into the design of novel molecules with antagonistic profile. To prove the validity of the pharmacophore hypothesized a virtual screening process was also carried out. The pharmacophore was used as query to identify new hits using diverse databases of molecules. The results of this study revealed a set of new

An interactive human carbonic anhydrase-II (hCA-II) receptor--pharmacophore molecular model & anti-convulsant activity of the designed and synthesized 5-amino-1,3,4-thiadiazole-2-thiol conjugated imine derivatives.

PubMed

Yusuf, Mohammad; Khan, Riaz A; Khan, Maria; Ahmed, Bahar

2013-05-01

New imines, derived from aromatic aldehyde, chalcones and 5-amino-1,3,4-thiadiazole-2-thiol exhibited promising anti-convulsant activity which is explained through chemo-biological interactions at receptor site producing the inhibition of human Carbonic Anhydrase-II enzyme (hCA-II) through the proposed pharmacophore model at molecular levels as basis for pharmacological activity. The compounds 5-{1-(4-Chlorophenyl)-3-[4-(methoxy-phenyl)-prop-2-en-1-ylidene]amino}-1,3,4-thiadiazole-2-thiol (2b), 5-{[1-(4-chloro-phenyl)]-3-[4-(dimethyl-amino-phenyl)-prop-2-en-1-ylidene]amino}-1,3,4-thiadiazole-2-thiol (2c) and 5-{[1-(4-chloro-phenyl)]-3-[(4-amino-phenyl)-prop-2-en-1-ylidene]amino}-1,3,4-thiadiazole-2-thiol (2f) showed 100% activity in comparison with standard Acetazolamide, a known anti-convulsant drug. The compounds 2c, 2f also passed the Rotarod and Ethanol Potentiation tests which further confirmed them to be safe in motor coordination activity and safe from generating neurological toxicity. © 2013 John Wiley & Sons A/S.

Discrete Dynamical Modeling.

ERIC Educational Resources Information Center

Sandefur, James T.

1991-01-01

Discussed is the process of translating situations involving changing quantities into mathematical relationships. This process, called dynamical modeling, allows students to learn new mathematics while sharpening their algebraic skills. A description of dynamical systems, problem-solving methods, a graphical analysis, and available classroom…

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.

Pharmacophore, QSAR, and binding mode studies of substrates of human cytochrome P450 2D6 (CYP2D6) using molecular docking and virtual mutations and an application to chinese herbal medicine screening.

PubMed

Mo, Sui-Lin; Liu, Wei-Feng; Li, Chun-Guang; Zhou, Zhi-Wei; Luo, Hai-Bin; Chew, Helen; Liang, Jun; Zhou, Shu-Feng

2012-07-01

The highly polymorphic human cytochrome P450 2D6 (CYP2D6) metabolizes about 25% of currently used drugs. In this study, we have explored the interaction of a large number of substrates (n = 120) with wild-type and mutated CYP2D6 by molecular docking using the CDOCKER module. Before we conducted the molecular docking and virtual mutations, the pharmacophore and QSAR models of CYP2D6 substrates were developed and validated. Finally, we explored the interaction of a traditional Chinese herbal formula, Fangjifuling decoction, with CYP2D6 by virtual screening. The optimized pharmacophore model derived from 20 substrates of CYP2D6 contained two hydrophobic features and one hydrogen bond acceptor feature, giving a relevance ratio of 76% when a validation set of substrates were tested. However, our QSAR models gave poor prediction of the binding affinity of substrates. Our docking study demonstrated that 117 out of 120 substrates could be docked into the active site of CYP2D6. Forty one out of 117 substrates (35.04%) formed hydrogen bonds with various active site residues of CYP2D6 and 53 (45.30%) substrates formed a strong π-π interaction with Phe120 (53/54), with only carvedilol showing π-π interaction with Phe483. The active site residues involving hydrogen bond formation with substrates included Leu213, Lys214, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, Phe483, and Phe484. Furthermore, the CDOCKER algorithm was further applied to study the impact of mutations of 28 active site residues (mostly non-conserved) of CYP2D6 on substrate binding modes using five probe substrates including bufuralol, debrisoquine, dextromethorphan, sparteine, and tramadol. All mutations of the residues examined altered the hydrogen bond formation and/or aromatic interactions, depending on the probe used in molecular docking. Apparent changes of the binding modes have been observed with the Glu216Asp and Asp301Glu mutants. Overall, 60 compounds out of 130 from Fangjifuling decoction

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

Modelling Holocene peatland dynamics with an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2017-05-01

Dynamic global vegetation models (DGVMs) are designed for the study of past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks. However, most DGVMs do not yet have detailed representations of permafrost and non-permafrost peatlands, which are an important store of carbon, particularly at high latitudes. We demonstrate a new implementation of peatland dynamics in a customized Arctic version of the LPJ-GUESS DGVM, simulating the long-term evolution of selected northern peatland ecosystems and assessing the effect of changing climate on peatland carbon balance. Our approach employs a dynamic multi-layer soil with representation of freeze-thaw processes and litter inputs from a dynamically varying mixture of the main peatland plant functional types: mosses, shrubs and graminoids. The model was calibrated and tested for a sub-Arctic mire in Stordalen, Sweden, and validated at a temperate bog site in Mer Bleue, Canada. A regional evaluation of simulated carbon fluxes, hydrology and vegetation dynamics encompassed additional locations spread across Scandinavia. Simulated peat accumulation was found to be generally consistent with published data and the model was able to capture reported long-term vegetation dynamics, water table position and carbon fluxes. A series of sensitivity experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We found that the Stordalen mire may be expected to sequester more carbon in the first half of the 21st century due to milder and wetter climate conditions, a longer growing season, and the CO2 fertilization effect, turning into a carbon source after mid-century because of higher decomposition rates in response to warming soils.

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.

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…

Modelling MIZ dynamics in a global model

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Molecular Quantum Similarity, Chemical Reactivity and Database Screening of 3D Pharmacophores of the Protein Kinases A, B and G from Mycobacterium tuberculosis.

PubMed

Morales-Bayuelo, Alejandro

2017-06-21

Mycobacterium tuberculosis remains one of the world's most devastating pathogens. For this reason, we developed a study involving 3D pharmacophore searching, selectivity analysis and database screening for a series of anti-tuberculosis compounds, associated with the protein kinases A, B, and G. This theoretical study is expected to shed some light onto some molecular aspects that could contribute to the knowledge of the molecular mechanics behind interactions of these compounds, with anti-tuberculosis activity. Using the Molecular Quantum Similarity field and reactivity descriptors supported in the Density Functional Theory, it was possible to measure the quantification of the steric and electrostatic effects through the Overlap and Coulomb quantitative convergence (alpha and beta) scales. In addition, an analysis of reactivity indices using global and local descriptors was developed, identifying the binding sites and selectivity on these anti-tuberculosis compounds in the active sites. Finally, the reported pharmacophores to PKn A, B and G, were used to carry out database screening, using a database with anti-tuberculosis drugs from the Kelly Chibale research group (http://www.kellychibaleresearch.uct.ac.za/), to find the compounds with affinity for the specific protein targets associated with PKn A, B and G. In this regard, this hybrid methodology (Molecular Mechanic/Quantum Chemistry) shows new insights into drug design that may be useful in the tuberculosis treatment today.

RELATING ACCUMULATOR MODEL PARAMETERS AND NEURAL DYNAMICS

PubMed Central

Purcell, Braden A.; Palmeri, Thomas J.

2016-01-01

Accumulator models explain decision-making as an accumulation of evidence to a response threshold. Specific model parameters are associated with specific model mechanisms, such as the time when accumulation begins, the average rate of evidence accumulation, and the threshold. These mechanisms determine both the within-trial dynamics of evidence accumulation and the predicted behavior. Cognitive modelers usually infer what mechanisms vary during decision-making by seeing what parameters vary when a model is fitted to observed behavior. The recent identification of neural activity with evidence accumulation suggests that it may be possible to directly infer what mechanisms vary from an analysis of how neural dynamics vary. However, evidence accumulation is often noisy, and noise complicates the relationship between accumulator dynamics and the underlying mechanisms leading to those dynamics. To understand what kinds of inferences can be made about decision-making mechanisms based on measures of neural dynamics, we measured simulated accumulator model dynamics while systematically varying model parameters. In some cases, decision- making mechanisms can be directly inferred from dynamics, allowing us to distinguish between models that make identical behavioral predictions. In other cases, however, different parameterized mechanisms produce surprisingly similar dynamics, limiting the inferences that can be made based on measuring dynamics alone. Analyzing neural dynamics can provide a powerful tool to resolve model mimicry at the behavioral level, but we caution against drawing inferences based solely on neural analyses. Instead, simultaneous modeling of behavior and neural dynamics provides the most powerful approach to understand decision-making and likely other aspects of cognition and perception. PMID:28392584

A Comparative Study on Selective PPAR Modulators through Quantitative Structure-activity Relationship, Pharmacophore and Docking Analyses.

PubMed

Nandy, Ashis; Roy, Kunal; Saha, Achintya

2018-01-01

Metabolic syndrome is a matrix of different metabolic disorders which are the leading cause of death in human beings. Peroxysome proliferated activated receptor (PPAR) is a nuclear receptor involved in metabolism of fats and glucose. In order to explore structural requirements for selective PPAR modulators to control lipid and carbohydrate metabolism, the multi-cheminformatics studies have been performed. In silico modeling studies have been performed on a diverse set of PPAR modulators through quantitative structure-activity relationship (QSAR), pharmacophore mapping and docking studies. It is observed that the presence of an amide fragment (-CONHRPh) has a detrimental effect while an aliphatic ether linkage has a beneficial effect on PPARα modulation. On the other hand, the presence of an amide fragment has a positive effect on PPARδ modulation, but the aliphatic ether linkage and substituted aromatic ring in the molecular scaffold are very much essential for imparting potent and selective PPARγ modulation. Negative ionizable features (i.e. polar fragments) must be present in PPARδ and α modulators, but a hydrophobic feature is the prime requirement for PPARγ modulation. Here, the essential structural features have been explored for selective modulation of each subtype of PPAR in order to design new modulators with improved activity/selectivity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structure-activity relationships of cannabinoids: A joint CoMFA and pseudoreceptor modelling study

NASA Astrophysics Data System (ADS)

Schmetzer, Silke; Greenidge, Paulette; Kovar, Karl-Artur; Schulze-Alexandru, Meike; Folkers, Gerd

1997-05-01

A cannabinoid pseudoreceptor model for the CB1-receptor has been constructed for 31 cannabinoids using the molecular modelling software YAK. Additionally, two CoMFA studies were performed on these ligands, the first of which was conducted prior to the building of the pseudoreceptor. Its pharmacophore is identical with the initial superposition of ligands used for pseudoreceptor construction. In contrast, the ligand alignment for the second CoMFA study was taken directly from the final cannabinoid pseudoreceptor model. This altered alignment gives markedly improved cross-validated r2 values as compared to those obtained from the original alignment with{{r}}_{{{cross}}}^2 values of 0.79 and 0.63, respectively, for five components. However, the pharmacophore alignment has the better predictive ability. Both the CoMFA and pseudoreceptor methods predict the free energy of binding of test ligands well.

Dynamic Modelling Of A SCARA Robot

NASA Astrophysics Data System (ADS)

Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

1987-10-01

This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

Screening and identification of potential PTP1B allosteric inhibitors using in silico and in vitro approaches.

PubMed

Shinde, Ranajit Nivrutti; Kumar, G Siva; Eqbal, Shahbaz; Sobhia, M Elizabeth

2018-01-01

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for Type 2 diabetes due to its specific role as a negative regulator of insulin signaling pathways. Discovery of active site directed PTP1B inhibitors is very challenging due to highly conserved nature of the active site and multiple charge requirements of the ligands, which makes them non-selective and non-permeable. Identification of the PTP1B allosteric site has opened up new avenues for discovering potent and selective ligands for therapeutic intervention. Interactions made by potent allosteric inhibitor in the presence of PTP1B were studied using Molecular Dynamics (MD). Computationally optimized models were used to build separate pharmacophore models of PTP1B and TCPTP, respectively. Based on the nature of interactions the target residues offered, a receptor based pharmacophore was developed. The pharmacophore considering conformational flexibility of the residues was used for the development of pharmacophore hypothesis to identify potentially active inhibitors by screening large compound databases. Two pharmacophore were successively used in the virtual screening protocol to identify potential selective and permeable inhibitors of PTP1B. Allosteric inhibition mechanism of these molecules was established using molecular docking and MD methods. The geometrical criteria values confirmed their ability to stabilize PTP1B in an open conformation. 23 molecules that were identified as potential inhibitors were screened for PTP1B inhibitory activity. After screening, 10 molecules which have good permeability values were identified as potential inhibitors of PTP1B. This study confirms that selective and permeable inhibitors can be identified by targeting allosteric site of PTP1B.

A combination of 2D similarity search, pharmacophore, and molecular docking techniques for the identification of vascular endothelial growth factor receptor-2 inhibitors.

PubMed

Ai, Guanhua; Tian, Caiping; Deng, Dawei; Fida, Guissi; Chen, Haiyan; Ma, Yuxiang; Ding, Li; Gu, Yueqing

2015-04-01

The human vascular endothelial growth factor receptor-2 (VEGFR-2) has been an attractive target for the inhibition of angiogenesis. In the current study, we used a hybrid protocol of virtual screening methods to retrieve new VEGFR-2 inhibitors from the Zinc-Specs Database (441 574 compounds). The hybrid protocol included the initial screening of candidates by comparing the 2D similarity to five reported top active inhibitors of 13 VEGFR-2 X-ray crystallography structures, followed by the pharmacophore modeling of virtual screening on the basis of receptor-ligand interactions and further narrowing by LibDOCK to obtain the final hits. Two compounds (AN-919/41439526 and AK-968/40939851) with a high libscore were selected as the final hits for a subsequent cell cytotoxicity study. The two compounds screened exerted significant inhibitory effects on the proliferation of cancer cells (U87 and MCF-7). The results indicated that the hybrid procedure is an effective approach for screening specific receptor inhibitors.

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

PubMed

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

2011-06-27

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

New 3D model for dynamics modeling

NASA Astrophysics Data System (ADS)

Perez, Alain

1994-05-01

The wrist articulation represents one of the most complex mechanical systems of the human body. It is composed of eight bones rolling and sliding along their surface and along the faces of the five metacarpals of the hand and the two bones of the arm. The wrist dynamics are however fundamental for the hand movement, but it is so complex that it still remains incompletely explored. This work is a part of a new concept of computer-assisted surgery, which consists in developing computer models to perfect surgery acts by predicting their consequences. The modeling of the wrist dynamics are based first on the static model of its bones in three dimensions. This 3D model must optimise the collision detection procedure which is the necessary step to estimate the physical contact constraints. As many other possible computer vision models do not fit with enough precision to this problem, a new 3D model has been developed thanks to the median axis of the digital distance map of the bones reconstructed volume. The collision detection procedure is then simplified for contacts are detected between spheres. The experiment of this original 3D dynamic model products realistic computer animation images of solids in contact. It is now necessary to detect ligaments on digital medical images and to model them in order to complete a wrist model.

Further studies on lead compounds containing the opioid pharmacophore Dmt-Tic.

PubMed

Balboni, Gianfranco; Fiorini, Stella; Baldisserotto, Anna; Trapella, Claudio; Sasaki, Yusuke; Ambo, Akihiro; Marczak, Ewa D; Lazarus, Lawrence H; Salvadori, Severo

2008-08-28

Some reference opioids containing the Dmt-Tic pharmacophore, especially the delta agonists H-Dmt-Tic-Gly-NH-Ph (1) and H-Dmt-Tic-NH-(S)CH(CH2-COOH)-Bid (4) (UFP-512) were evaluated for the influence of the substitution of Gly with aspartic acid, its chirality, and the importance of the -NH-Ph and N(1)H-Bid hydrogens in the inductions of delta agonism. The results provide the following conclusions: (i) Asp increases delta selectivity by lowering the mu affinity; (ii) -NH-Ph and N(1)H-Bid nitrogens methylation transforms the delta agonists into delta antagonists; (iii) the substitution of Gly with L-Asp/D-Asp in the delta agonist H-Dmt-Tic-Gly-NH-Ph gave delta antagonists; the same substitution in the delta agonist H-Dmt-Tic-NH-CH2-Bid yielded more selective agonists, H-Dmt-Tic-NH-(S)CH(CH2-COOH)-Bid and H-Dmt-Tic-NH-(R)CH(CH2-COOH)-Bid; (iv) L-Asp seems important only in functional bioactivity, not in receptor affinity; (v) H-Dmt-Tic-NH-(S)CH(CH2-COOH)-Bid(N(1)-Me) (10) evidenced analgesia similar to 4, which was reversed by naltrindole only in the tail flick. 4 and 10 had opposite behaviours in mice; 4 caused agitation, 10 gave sedation and convulsions.

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.

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability

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

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

Are 1,4- and 1,5-disubstituted 1,2,3-triazoles good pharmacophoric groups?

PubMed

Massarotti, Alberto; Aprile, Silvio; Mercalli, Valentina; Del Grosso, Erika; Grosa, Giorgio; Sorba, Giovanni; Tron, Gian Cesare

2014-11-01

Over the last decade, 1,2,3-triazoles have received increasing attention in medicinal chemistry thanks to the discovery of the highly useful and widely applicable 1,3-dipolar cycloaddition reaction between azides and alkynes (click chemistry) catalyzed by copper salts and ruthenium complexes. After a decade of medicinal chemistry research on 1,2,3-triazoles, we feel that the time is ripe to demonstrate the real ability of this heterocycle to participate in important and pivotal binding interactions with biological targets while maintaining a good pharmacokinetic profile. In this study, we retrieved and analyzed X-ray crystal structures of complexes between 1,2,3-triazoles and either proteins or DNA to understand the pharmacophoric role of the triazole. Furthermore, the metabolic stability, the capacity to inhibit cytochromes, and the contribution of 1,2,3-triazoles to the overall aqueous solubility of compounds containing them have been analyzed. This information should furnish fresh insight for medicinal chemists in the design of novel bioactive molecules that contain the triazole nucleus. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pharmacophore based design of some multi-targeted compounds targeted against pathways of diabetic complications.

PubMed

Chadha, Navriti; Silakari, Om

2017-09-01

Diabetic complications is a complex metabolic disorder developed primarily due to prolonged hyperglycemia in the body. The complexity of the disease state as well as the unifying pathophysiology discussed in the literature reports exhibited that the use of multi-targeted agents with multiple complementary biological activities may offer promising therapy for the intervention of the disease over the single-target drugs. In the present study, novel thiazolidine-2,4-dione analogues were designed as multi-targeted agents implicated against the molecular pathways involved in diabetic complications using knowledge based as well as in-silico approaches such as pharmacophore mapping, molecular docking etc. The hit molecules were duly synthesized and biochemical estimation of these molecules against aldose reductase (ALR2), protein kinase Cβ (PKCβ) and poly (ADP-ribose) polymerase 1 (PARP-1) led to identification of compound 2 that showed good potency against PARP-1 and ALR2 enzymes. These positive results support the progress of a low cost multi-targeted agent with putative roles in diabetic complications. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

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

An individual-based model of zebrafish population dynamics accounting for energy dynamics.

PubMed

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

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.

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.

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

NASA Astrophysics Data System (ADS)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

Dynamic Models of Insurgent Activity

DTIC Science & Technology

2014-05-19

Martin Short, P. Jeffrey Brantingham, Frederick Schoenberg, George Tita . Self-Exciting Point Process Modeling of Crime, Journal of the American...Mohler, P. J. Brantingham, G. E. Tita . Gang rivalry dynamics via coupled point process networks, Discrete and Continuous Dynamical Systems - Series...8532-2-1 Laura Smith, Andrea Bertozzi, P. Jeffrey Brantingham, George Tita , Matthew Valasik. ADAPTATION OF AN ECOLOGICAL TERRITORIAL MODEL TOSTREET

An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

PubMed Central

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409

Supply based on demand dynamical model

NASA Astrophysics Data System (ADS)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

Modeling Dynamic Regulatory Processes in Stroke.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

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 developmore » 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.« less

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

PubMed

Kim, J; Lee, C; Chong, Y

2009-01-01

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

Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.

2012-12-01

In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the

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.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

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.

Overview of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Regan, Timothy F.

2004-01-01

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

Structural basis for ligand recognition at the benzodiazepine binding site of GABAA alpha 3 receptor, and pharmacophore-based virtual screening approach.

PubMed

Vijayan, R S K; Ghoshal, Nanda

2008-10-01

Given the heterogeneity of GABA(A) receptor, the pharmacological significance of identifying subtype selective modulators is increasingly being recognized. Thus, drugs selective for GABA(A) alpha(3) receptors are expected to display fewer side effects than the drugs presently in clinical use. Hence we carried out 3D QSAR (three-dimensional quantitative structure-activity relationship) studies on a series of novel GABA(A) alpha(3) subtype selective modulators to gain more insight into subtype affinity. To identify the 3D functional attributes required for subtype selectivity, a chemical feature-based pharmacophore, primarily based on selective ligands representing diverse structural classes was generated. The obtained pseudo receptor model of the benzodiazepine binding site revealed a binding mode akin to "Message-Address" concept. Scaffold hopping was carried out across multi-conformational May Bridge database for the identification of novel chemotypes. Further a focused data reduction approach was employed to choose a subset of enriched compounds based on "Drug likeness" and "Similarity-based" methods. These results taken together could provide impetus for rational design and optimization of more selective and high affinity leads with a potential to have decreased adverse effects.

A Lagrangian dynamic subgrid-scale model turbulence

NASA Technical Reports Server (NTRS)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

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.

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.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

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. Published by Elsevier Inc.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the

Coupling population dynamics with earth system models: the POPEM model.

PubMed

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

Swarm Intelligence for Urban Dynamics Modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

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.

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.

Aegeline inspired synthesis of novel β3-AR agonist improves insulin sensitivity in vitro and in vivo models of insulin resistance.

PubMed

Rajan, Sujith; Satish, Sabbu; Shankar, Kripa; Pandeti, Sukanya; Varshney, Salil; Srivastava, Ankita; Kumar, Durgesh; Gupta, Abhishek; Gupta, Sanchita; Choudhary, Rakhi; Balaramnavar, Vishal M; Narender, Tadigoppula; Gaikwad, Anil N

2018-03-07

In our drug discovery program of natural product, earlier we have reported Aegeline that is N-acylated-1-amino-2- alcohol, which was isolated from the leaves of Aeglemarmelos showed anti-hyperlipidemic activity for which the QSAR studies predicted the compound to be the β3-AR agonist, but the mechanism of its action was not elucidated. In our present study, we have evaluated the β3-AR activity of novel N-acyl-1-amino-3-arylopropanol synthetic mimics of aegeline and its beneficial effect in insulin resistance. In this study, we have proposed the novel pharmacophore model using reported molecules for antihyperlipidemic activity. The reported pharmacophore features were also compared with the newly developed pharmacophore model for the observed biological activity. Based on 3D pharmacophore modeling of known β3AR agonist, we screened 20 synthetic derivatives of Aegeline from the literature. From these, the top scoring compound 10C was used for further studies. The in-slico result was further validated in HEK293T cells co-trransfected with human β3-AR and CRE-Luciferase reporter plasmid for β3-AR activity.The most active compound was selected and β3-AR activity was further validated in white and brown adipocytes differentiated from human mesenchymal stem cells (hMSCs). Insulin resistance model developed in hMSC derived adipocytes was used to study the insulin sensitizing property. 8 week HFD fed C57BL6 mice was given 50 mg/Kg of the selected compound and metabolic phenotyping was done to evaluate its anti-diabetic effect. As predicted by in-silico 3D pharmacophore modeling, the compound 10C was found to be the most active and specific β3-AR agonist with EC 50 value of 447 nM. The compound 10C activated β3AR pathway, induced lipolysis, fatty acid oxidation and increased oxygen consumption rate (OCR) in human adipocytes. Compound 10C induced expression of brown adipocytes specific markers and reverted chronic insulin induced insulin resistance in white

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

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

2011-01-01

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

Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models

NASA Astrophysics Data System (ADS)

Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C.; Noé, Frank

2013-11-01

The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.

The AFDD International Dynamic Stall Workshop on Correlation of Dynamic Stall Models with 3-D Dynamic Stall Data

NASA Technical Reports Server (NTRS)

Tan, C. M.; Carr, L. W.

1996-01-01

A variety of empirical and computational fluid dynamics two-dimensional (2-D) dynamic stall models were compared to recently obtained three-dimensional (3-D) dynamic stall data in a workshop on modeling of 3-D dynamic stall of an unswept, rectangular wing, of aspect ratio 10. Dynamic stall test data both below and above the static stall angle-of-attack were supplied to the participants, along with a 'blind' case where only the test conditions were supplied in advance, with results being compared to experimental data at the workshop itself. Detailed graphical comparisons are presented in the report, which also includes discussion of the methods and the results. The primary conclusion of the workshop was that the 3-D effects of dynamic stall on the oscillating wing studied in the workshop can be reasonably reproduced by existing semi-empirical models once 2-D dynamic stall data have been obtained. The participants also emphasized the need for improved quantification of 2-D dynamic stall.

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

Dynamics Modelling of Biolistic Gene Guns

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 formore » improving and manipulating performance of the biolistic gene gun.« less

Social Dynamics Modeling and Inference

DTIC Science & Technology

2018-03-29

AFRL-AFOSR-JP-TR-2018-0027 Social Dynamics Modeling and Inference Kwang-Cheng Chen NATIONAL TAIWAN UNIVERSITY Final Report 03/29/2018 DISTRIBUTION A...DATES COVERED (From - To)      14 May 2014 to 13 May 2017 4.  TITLE AND SUBTITLE Social Dynamics Modeling and Inference 5a.  CONTRACT NUMBER 5b.  GRANT...behavior in human society, to set up the foundation of future possible inference and even control of social collective behavior. Two primary

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

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

Identification of potential hit compounds for Dengue virus NS2B/NS3 protease inhibitors by combining virtual screening and binding free energy calculations.

PubMed

Wichapong, K; Nueangaudom, A; Pianwanit, S; Sippl, W; Kokpol, S

2013-09-01

Dengue virus (DV) infections are a serious public health problem and there is currently no vaccine or drug treatment. NS2B/NS3 protease, an essential enzyme for viral replication, is one of the promising targets in the search for drugs against DV. In this research work, virtual screening (VS) was carried out on four multi-conformational databases using several criteria. Firstly, molecular dynamics simulations of the NS2B/NS3 protease and four known inhibitors, which reveal an importance of both electrostatic and van der Waals interactions in stabilizing the ligand-enzyme interaction, were used to generate three different pharmacophore models (a structure-based, a static and a dynamic). Subsequently, these three models were employed for pharmacophore search in the VS. Secondly, compounds passing the first criterion were further reduced using the Lipinski's rule of five to keep only compounds with drug-like properties. Thirdly, molecular docking calculations were performed to remove compounds with unsuitable ligand-enzyme interactions. Finally, binding free energy of each compound was calculated. Compounds having better energy than the known inhibitors were selected and thus 20 potential hits were obtained.

Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics.

PubMed

Xia, Yingcun; Bjørnstad, Ottar N; Grenfell, Bryan T

2004-08-01

Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer-resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible-infected-recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.

A Dynamic Model of Sustainment Investment

DTIC Science & Technology

2015-02-01

Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

Modelling, simulation and applications of longitudinal train dynamics

NASA Astrophysics Data System (ADS)

Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

2017-10-01

Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

System Dynamics Modeling for Supply Chain Information Sharing

NASA Astrophysics Data System (ADS)

Feng, Yang

In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

The Challenges to Coupling Dynamic Geospatial Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 Urbanizationmore » 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.« less

Fractional-order in a macroeconomic dynamic model

NASA Astrophysics Data System (ADS)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

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.

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.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

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.

Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

PubMed

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Multiple Ligands Targeting Cholinesterases and β-Amyloid: Synthesis, Biological Evaluation of Heterodimeric Compounds with Benzylamine Pharmacophore.

PubMed

Szałaj, Natalia; Bajda, Marek; Dudek, Katarzyna; Brus, Boris; Gobec, Stanislav; Malawska, Barbara

2015-08-01

Alzheimer's disease (AD) is a fatal and complex neurodegenerative disorder for which effective treatment remains the unmet challenge. Using donepezil as a starting point, we aimed to develop novel potential anti-AD agents with a multidirectional biological profile. We designed the target compounds as dual binding site acetylcholinesterase inhibitors, where the N-benzylamine pharmacophore is responsible for interactions with the catalytic anionic site of the enzyme. The heteroaromatic fragment responsible for interactions with the peripheral anionic site was modified and three different heterocycles were introduced: isoindoline, isoindolin-1-one, and saccharine. Based on the results of the pharmacological evaluation, we identified compound 8b with a saccharine moiety as the most potent and selective human acetylcholinesterase inhibitor (IC50  = 33 nM) and beta amyloid aggregation inhibitor. It acts as a non-competitive acetylcholinesterase inhibitor and is able to cross the blood-brain barrier in vitro. We believe that compound 8b represents an important lead compound for further development as potential anti-AD agent. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovery of a Small-Molecule Inhibitor of Interleukin 15: Pharmacophore-Based Virtual Screening and Hit Optimization.

PubMed

Quéméner, Agnès; Maillasson, Mike; Arzel, Laurence; Sicard, Benoit; Vomiandry, Romy; Mortier, Erwan; Dubreuil, Didier; Jacques, Yannick; Lebreton, Jacques; Mathé-Allainmat, Monique

2017-07-27

Interleukin (IL)-15 is a pleiotropic cytokine, which is structurally close to IL-2 and shares with it the IL-2 β and γ receptor (R) subunits. By promoting the activation and proliferation of NK, NK-T, and CD8+ T cells, IL-15 plays important roles in innate and adaptative immunity. Moreover, the association of high levels of IL-15 expression with inflammatory and autoimmune diseases has led to the development of various antagonistic approaches targeting IL-15. This study is an original approach aimed at discovering small-molecule inhibitors impeding IL-15/IL-15R interaction. A pharmacophore and docking-based virtual screening of compound libraries led to the selection of 240 high-scoring compounds, 36 of which were found to bind IL-15, to inhibit the binding of IL-15 to the IL-2Rβ chain or the proliferation of IL-15-dependent cells or both. One of them was selected as a hit and optimized by a structure-activity relationship approach, leading to the first small-molecule IL-15 inhibitor with sub-micromolar activity.

Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

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.

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

Automated adaptive inference of phenomenological dynamical models

NASA Astrophysics Data System (ADS)

Daniels, Bryan

Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

Computational study of the inhibitory mechanism of the kinase CDK5 hyperactivity by peptide p5 and derivation of a pharmacophore

NASA Astrophysics Data System (ADS)

Cardone, A.; Brady, M.; Sriram, R.; Pant, H. C.; Hassan, S. A.

2016-06-01

The hyperactivity of the cyclic dependent kinase 5 (CDK5) induced by the activator protein p25 has been linked to a number of pathologies of the brain. The CDK5-p25 complex has thus emerged as a major therapeutic target for Alzheimer's disease (AD) and other neurodegenerative conditions. Experiments have shown that the peptide p5 reduces the CDK5-p25 activity without affecting the endogenous CDK5-p35 activity, whereas the peptide TFP5, obtained from p5, elicits similar inhibition, crosses the blood-brain barrier, and exhibits behavioral rescue of AD mice models with no toxic side effects. The molecular basis of the kinase inhibition is not currently known, and is here investigated by computer simulations. It is shown that p5 binds the kinase at the same CDK5/p25 and CDK5/p35 interfaces, and is thus a non-selective competitor of both activators, in agreement with available experimental data in vitro. Binding of p5 is enthalpically driven with an affinity estimated in the low µM range. A quantitative description of the binding site and pharmacophore is presented, and options are discussed to increase the binding affinity and selectivity in the design of drug-like compounds against AD.

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

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.

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

Combination of virtual screening protocol by in silico towards the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors

NASA Astrophysics Data System (ADS)

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2018-02-01

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is a potent new bleaching herbicide target. Therefore, in silico structure-based virtual screening was performed in order to speed up the identification of promising HPPD inhibitors. In this study, an integrated virtual screening protocol by combining 3D-pharmacophore model, molecular docking and molecular dynamics (MD) simulation was established to find novel HPPD inhibitors from four commercial databases. 3D-pharmacophore Hypo1 model was applied to efficiently narrow potential hits. The hit compounds were subsequently submitted to molecular docking studies, showing four compounds as potent inhibitor with the mechanism of the Fe(II) coordination and interaction with Phe360, Phe403 and Phe398. MD result demonstrated that nonpolar term of compound 3881 made great contributions to binding affinities. It showed an IC50 being 2.49 µM against AtHPPD in vitro. The results provided useful information for developing novel HPPD inhibitors, leading to further understanding of the interaction mechanism of HPPD inhibitors.

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

Complex networks under dynamic repair model

NASA Astrophysics Data System (ADS)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

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.

Generic solar photovoltaic system dynamic simulation model specification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intendedmore » to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.« less

Identification of the minimum pharmacophore of lipid-phosphatidylserine (PS) binding peptide-peptoid hybrid PPS1D1.

PubMed

Singh, Jaspal; Shukla, Satya Prakash; Desai, Tanvi J; Udugamasooriya, D Gomika

2016-09-15

We previously reported a unique peptide-peptoid hybrid, PPS1 that specifically recognizes lipid-phosphatidylserine (PS) and a few other negatively charged phospholipids, but not neutral phospholipids, on the cell membrane. The dimeric version of PPS1, i.e., PPS1D1 triggers strong cancer cell cytotoxicity and has been validated in lung cancer models both in vitro and in vivo. Given that PS and other negatively charged phospholipids are abundant in almost all tumor microenvironments, PPS1D1 is an attractive drug lead that can be developed into a globally applicable anti-cancer agent. Therefore, it is extremely important to identify the minimum pharmacophore of PPS1D1. In this study, we have synthesized alanine/sarcosine derivatives as well as truncated derivatives of PPS1D1. We performed ELISA-like competitive binding assay to evaluate the PS-recognition potential and standard MTS cell viability assay on HCC4017 lung cancer cells to validate the cell cytotoxicity effects of these derivatives. Our studies indicate that positively charged residues at the second and third positions, as well as four hydrophobic residues at the fifth through eighth positions, are imperative for the binding and activity of PPS1D1. Methionine at the first position was not essential, whereas the positively charged Nlys at the fourth position was minimally needed, as two derivatives that were synthesized replacing this residue were almost as active as PPS1D1. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Dynamical features of an anisotropic cosmological model

NASA Astrophysics Data System (ADS)

Mishra, B.; Tarai, Sankarsan; Tripathy, S. K.

2018-04-01

The dynamical features of Bianchi type VI_h (BVI_h) universe are investigated in f(R, T) theory of gravity. The field equations and the physical properties of the model are derived considering a power law expansion of the universe. The effect of anisotropy on the dynamics of the universe as well as on the energy conditions are studied. The assumed anisotropy of the model is found to have substantial effects on the energy conditions and dynamical parameters.

Modeling Gas Dynamics in California Sea Lions

DTIC Science & Technology

2015-09-30

W. and Fahlman, A. (2009). Could beaked whales get the bends?. Effect of diving behaviour and physiology on modelled gas exchange for three species...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Modeling Gas Dynamics in California Sea Lions Andreas...to update a current gas dynamics model with recently acquired data for respiratory compliance (P-V), and body compartment size estimates in

Flexible aircraft dynamic modeling for dynamic analysis and control synthesis

NASA Technical Reports Server (NTRS)

Schmidt, David K.

1989-01-01

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

Local dynamic subgrid-scale models in channel flow

NASA Technical Reports Server (NTRS)

Cabot, William H.

1994-01-01

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

A non-linear mathematical model for dynamic analysis of spur gears including shaft and bearing dynamics

NASA Technical Reports Server (NTRS)

Ozguven, H. Nevzat

1991-01-01

A six-degree-of-freedom nonlinear semi-definite model with time varying mesh stiffness has been developed for the dynamic analysis of spur gears. The model includes a spur gear pair, two shafts, two inertias representing load and prime mover, and bearings. As the shaft and bearing dynamics have also been considered in the model, the effect of lateral-torsional vibration coupling on the dynamics of gears can be studied. In the nonlinear model developed several factors such as time varying mesh stiffness and damping, separation of teeth, backlash, single- and double-sided impacts, various gear errors and profile modifications have been considered. The dynamic response to internal excitation has been calculated by using the 'static transmission error method' developed. The software prepared (DYTEM) employs the digital simulation technique for the solution, and is capable of calculating dynamic tooth and mesh forces, dynamic factors for pinion and gear, dynamic transmission error, dynamic bearing forces and torsions of shafts. Numerical examples are given in order to demonstrate the effect of shaft and bearing dynamics on gear dynamics.

Dynamic Modeling of the SMAP Rotating Flexible Antenna

NASA Technical Reports Server (NTRS)

Nayeri, Reza D.

2012-01-01

Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications

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

PubMed

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

2014-01-01

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

Dynamic and Structural Gas Turbine Engine Modeling

NASA Technical Reports Server (NTRS)

Turso, James A.

2003-01-01

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

Three dimensional model of severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain and molecular design of severe acute respiratory syndrome coronavirus helicase inhibitors

NASA Astrophysics Data System (ADS)

Hoffmann, Marcin; Eitner, Krystian; von Grotthuss, Marcin; Rychlewski, Leszek; Banachowicz, Ewa; Grabarkiewicz, Tomasz; Szkoda, Tomasz; Kolinski, Andrzej

2006-05-01

The modeling of the severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain was performed using the protein structure prediction Meta Server and the 3D Jury method for model selection, which resulted in the identification of 1JPR, 1UAA and 1W36 PDB structures as suitable templates for creating a full atom 3D model. This model was further utilized to design small molecules that are expected to block an ATPase catalytic pocket thus inhibit the enzymatic activity. Binding sites for various functional groups were identified in a series of molecular dynamics calculation. Their positions in the catalytic pocket were used as constraints in the Cambridge structural database search for molecules having the pharmacophores that interacted most strongly with the enzyme in a desired position. The subsequent MD simulations followed by calculations of binding energies of the designed molecules were compared to ATP identifying the most successful candidates, for likely inhibitors—molecules possessing two phosphonic acid moieties at distal ends of the molecule.

Model for macroevolutionary dynamics.

PubMed

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

2013-07-02

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

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

PubMed

Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

2018-01-01

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

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

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.

Fractional Relativistic Yamaleev Oscillator Model and Its Dynamical Behaviors

NASA Astrophysics Data System (ADS)

Luo, Shao-Kai; He, Jin-Man; Xu, Yan-Li; Zhang, Xiao-Tian

2016-07-01

In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system.

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.

Dynamics in Higher Education Politics: A Theoretical Model

ERIC Educational Resources Information Center

Kauko, Jaakko

2013-01-01

This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…

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.

Exploring tropical forest vegetation dynamics using the FATES model

NASA Astrophysics Data System (ADS)

Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.

2017-12-01

Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.

Minimalist hybrid ligand/receptor-based pharmacophore model for CXCR4 applied to a small-library of marine natural products led to the identification of phidianidine a as a new CXCR4 ligand exhibiting antagonist activity.

PubMed

Vitale, Rosa Maria; Gatti, Monica; Carbone, Marianna; Barbieri, Federica; Felicità, Vera; Gavagnin, Margherita; Florio, Tullio; Amodeo, Pietro

2013-12-20

Here, we present a minimal hybrid ligand/receptor-based pharmacophore model (PM) for CXCR4, a chemokine receptor deeply involved in several pathologies, such as HIV infection, rheumatoid arthritis, cancer development/progression, and metastasization. This model, considerably simpler than those thus far proposed for this receptor, has been used to search for new CXCR4 inhibitors in a small marine natural product library available at ICB-CNR Institute (Pozzuoli, NA, Italy), since natural products, with their naturally selected chemical and functional diversity, represent a rich source of bioactive scaffolds; computational approaches allow searching for new scaffolds with a minimal waste of possibly precious natural product samples; and our "stripped-down" model substantially increases the probabilities of identifying potential hits even in small-sized libraries. This search, also validated by a systematic virtual screening of the same library, has led to the identification of a new CXCR4 ligand, phidianidine A (PHIA). Docking studies supported PHIA activity and suggested its possible binding modes to CXCR4. Using the CXCR4-expressing/CXCR7-negative GH4C1 cell line we show that PHIA inhibits CXCL12-induced DNA synthesis, cell migration, and ERK1/2 activation. The specificity of these effects was confirmed by the lack of PHIA activity in GH4C1 cells, in which siRNA highly reduces CXCR4 expression and the lack of cytoxicity of PHIA was also verified. Thus, PHIA represents a promising lead for a new family of CXCR4 modulators with wide margins of improvement in potency and specificity offered by the small and very simple underlying PM.

A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, J. Richard; Dunham, Steve; Mochalkin, Igor

2009-06-25

As the need for novel antibiotic classes to combat bacterial drug resistance increases, the paucity of leads resulting from target-based antibacterial screening of pharmaceutical compound libraries is of major concern. One explanation for this lack of success is that antibacterial screening efforts have not leveraged the eukaryotic bias resulting from more extensive chemistry efforts targeting eukaryotic gene families such as G protein-coupled receptors and protein kinases. Consistent with a focus on antibacterial target space resembling these eukaryotic targets, we used whole-cell screening to identify a series of antibacterial pyridopyrimidines derived from a protein kinase inhibitor pharmacophore. In bacteria, the pyridopyrimidinesmore » target the ATP-binding site of biotin carboxylase (BC), which catalyzes the first enzymatic step of fatty acid biosynthesis. These inhibitors are effective in vitro and in vivo against fastidious Gram-negative pathogens including Haemophilus influenzae. Although the BC active site has architectural similarity to those of eukaryotic protein kinases, inhibitor binding to the BC ATP-binding site is distinct from the protein kinase-binding mode, such that the inhibitors are selective for bacterial BC. In summary, we have discovered a promising class of potent antibacterials with a previously undescribed mechanism of action. In consideration of the eukaryotic bias of pharmaceutical libraries, our findings also suggest that pursuit of a novel inhibitor leads for antibacterial targets with active-site structural similarity to known human targets will likely be more fruitful than the traditional focus on unique bacterial target space, particularly when structure-based and computational methodologies are applied to ensure bacterial selectivity.« less

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

System dynamic modeling: an alternative method for budgeting.

PubMed

Srijariya, Witsanuchai; Riewpaiboon, Arthorn; Chaikledkaew, Usa

2008-03-01

To construct, validate, and simulate a system dynamic financial model and compare it against the conventional method. The study was a cross-sectional analysis of secondary data retrieved from the National Health Security Office (NHSO) in the fiscal year 2004. The sample consisted of all emergency patients who received emergency services outside their registered hospital-catchments area. The dependent variable used was the amount of reimbursed money. Two types of model were constructed, namely, the system dynamic model using the STELLA software and the multiple linear regression model. The outputs of both methods were compared. The study covered 284,716 patients from various levels of providers. The system dynamic model had the capability of producing various types of outputs, for example, financial and graphical analyses. For the regression analysis, statistically significant predictors were composed of service types (outpatient or inpatient), operating procedures, length of stay, illness types (accident or not), hospital characteristics, age, and hospital location (adjusted R(2) = 0.74). The total budget arrived at from using the system dynamic model and regression model was US$12,159,614.38 and US$7,301,217.18, respectively, whereas the actual NHSO reimbursement cost was US$12,840,805.69. The study illustrated that the system dynamic model is a useful financial management tool, although it is not easy to construct. The model is not only more accurate in prediction but is also more capable of analyzing large and complex real-world situations than the conventional method.

Dynamic Evolution Model Based on Social Network Services

NASA Astrophysics Data System (ADS)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics

NASA Astrophysics Data System (ADS)

Li, C. James; Lee, Hyungdae

2005-07-01

This paper presents a model-based method that predicts remaining useful life of a gear with a fatigue crack. The method consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffness; a gear dynamic model to simulate gear meshing dynamics and determine the dynamic load on the cracked tooth; and a fast crack propagation model to forecast the remaining useful life based on the estimated crack size and dynamic load. The fast crack propagation model was established to avoid repeated calculations of FEM and facilitate field deployment of the proposed method. Experimental studies were conducted to validate and demonstrate the feasibility of the proposed method for prognosis of a cracked gear.

Optimal post-experiment estimation of poorly modeled dynamic systems

NASA Technical Reports Server (NTRS)

Mook, D. Joseph

1988-01-01

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Modeling Firn Compaction in Dynamic Regions

NASA Astrophysics Data System (ADS)

Horlings, Annika N.; Christianson, Knut; Waddington, Edwin D.; Stevens, C. Max; Holschuh, Nicholas

2017-04-01

Firn compaction remains the largest source of uncertainty in assessments of ice-sheet mass balance from repeat altimetry measurements due to our limited understanding of the physical processes responsible for the transformation of snow into ice. In addition to the lack of a comprehensive, physically-based constitutive relationship that describes firn compaction, dynamic thinning is an important process in some regions, but is generally neglected in firn-compaction models due to their one-dimensional nature. Here, we report on preliminary results incorporating dynamic strain thinning into firn compaction models. Using a Lagrangian (material-following) reference frame, we first compact each firn element using a standard 1-D firn-compaction model without longitudinal strain. Then, we stretch each firn parcel at each time step by applying a prescribed longitudinal strain rate in the absence of further density changes; this produces additional vertical thinning. To assess variations among firn models, we compare results from eight firn densification models currently included in the UW Community Firn Model. We focus on the Northeast Greenland Ice Stream due to the high extensile strain rates (10-3 yr-1 or higher) in the ice stream's shear margins and the extensive firn-density data in this area from seismic measurements and shallow firn/ice cores. For temperatures and accumulation rates typical for northeast Greenland, our preliminary results indicate up to an 18-meter decrease in bubble close-off depth in the shear margins compared to nearby areas either inside or outside the ice stream, which compares favorably to field data. Further work includes incorporating physically-based constitutive relations and applying these improved models to other dynamic regions, such as the Amundsen Sea Embayment, where dynamic strain thinning has accelerated in recent decades.

Analysis of the Glutamate Agonist LY404,039 Binding to Nonstatic Dopamine Receptor D2 Dimer Structures and Consensus Docking.

PubMed

Salmas, Ramin Ekhteiari; Seeman, Philip; Aksoydan, Busecan; Erol, Ismail; Kantarcioglu, Isik; Stein, Matthias; Yurtsever, Mine; Durdagi, Serdar

2017-06-21

Dopamine receptor D2 (D2R) plays an important role in the human central nervous system and is a focal target of antipsychotic agents. The D2 High R and D2 Low R dimeric models previously developed by our group are used to investigate the prediction of binding affinity of the LY404,039 ligand and its binding mechanism within the catalytic domain. The computational data obtained using molecular dynamics simulations fit well with the experimental results. The calculated binding affinities of LY404,039 using MM/PBSA for the D2 High R and D2 Low R targets were -12.04 and -9.11 kcal/mol, respectively. The experimental results suggest that LY404,039 binds to D2 High R and D2 Low R with binding affinities (K i ) of 8.2 and 1640 nM, respectively. The high binding affinity of LY404,039 in terms of binding to [ 3 H]domperidone was inhibited by the presence of a guanine nucleotide, indicating an agonist action of the drug at D2 High R. The interaction analysis demonstrated that while Asp114 was among the most critical amino acids for D2 High R binding, residues Ser193 and Ser197 were significantly more important within the binding cavity of D2 Low R. Molecular modeling analyses are extended to ensemble docking as well as structure-based pharmacophore model (E-pharmacophore) development using the bioactive conformation of LY404,039 at the binding pocket as a template and screening of small-molecule databases with derived pharmacophore models.

Direct modeling for computational fluid dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun

2015-06-01

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

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

A micromechanical constitutive model for the dynamic response of brittle materials "Dynamic response of marble"

NASA Astrophysics Data System (ADS)

Haberman, Keith

2001-07-01

A micromechanically based constitutive model for the dynamic inelastic behavior of brittle materials, specifically "Dionysus-Pentelicon marble" with distributed microcracking is presented. Dionysus-Pentelicon marble was used in the construction of the Parthenon, in Athens, Greece. The constitutive model is a key component in the ability to simulate this historic explosion and the preceding bombardment form cannon fire that occurred at the Parthenon in 1678. Experiments were performed by Rosakis (1999) that characterized the static and dynamic response of this unique material. A micromechanical constitutive model that was previously successfully used to model the dynamic response of granular brittle materials is presented. The constitutive model was fitted to the experimental data for marble and reproduced the experimentally observed basic uniaxial dynamic behavior quite well. This micromechanical constitutive model was then implemented into the three dimensional nonlinear lagrangain finite element code Dyna3d(1998). Implementing this methodology into the three dimensional nonlinear dynamic finite element code allowed the model to be exercised on several preliminary impact experiments. During future simulations, the model is to be used in conjunction with other numerical techniques to simulate projectile impact and blast loading on the Dionysus-Pentelicon marble and on the structure of the Parthenon.

Dynamic intersectoral models with power-law memory

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.

Modelling oxygen transfer using dynamic alpha factors.

PubMed

Jiang, Lu-Man; Garrido-Baserba, Manel; Nolasco, Daniel; Al-Omari, Ahmed; DeClippeleir, Haydee; Murthy, Sudhir; Rosso, Diego

2017-11-01

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model of THz Magnetization Dynamics.

PubMed

Bocklage, Lars

2016-03-09

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.

Fluid Dynamics Lagrangian Simulation Model

NASA Astrophysics Data System (ADS)

Hyman, Ellis

1994-02-01

The work performed by Science Applications International Corporation (SAIC) on this contract, Fluid Dynamics Lagrangian Simulation Model, Contract Number N00014-89-C-2106, SAIC Project Number 01-0157-03-0768, focused on a number of research topics in fluid dynamics. The work was in support of the programs of NRL's Laboratory for Computational Physics and Fluid Dynamics and covered the period from 10 September 1989 to 9 December 1993. In the following sections, we describe each of the efforts and the results obtained. Much of the research work has resulted in journal publications. These are included in Appendices of this report for which the reader is referred for complete details.

Design, synthesis and screening studies of potent thiazol-2-amine derivatives as fibroblast growth factor receptor 1 inhibitors.

PubMed

Kumar, B V S Suneel; Lakshmi, Narasu; Kumar, M Ravi; Rambabu, Gundla; Manjashetty, Thimmappa H; Arunasree, Kalle M; Sriram, Dharmarajan; Ramkumar, Kavya; Neamati, Nouri; Dayam, Raveendra; Sarma, J A R P

2014-01-01

Fibroblast growth factor receptor 1 (FGFR1) a tyrosine kinase receptor, plays important roles in angiogenesis, embryonic development, cell proliferation, cell differentiation, and wound healing. The FGFR isoforms and their receptors (FGFRs) considered as a potential targets and under intense research to design potential anticancer agents. Fibroblast growth factors (FGF's) and its growth factor receptors (FGFR) plays vital role in one of the critical pathway in monitoring angiogenesis. In the current study, quantitative pharmacophore models were generated and validated using known FGFR1 inhibitors. The pharmacophore models were generated using a set of 28 compounds (training). The top pharmacophore model was selected and validated using a set of 126 compounds (test set) and also using external validation. The validated pharmacophore was considered as a virtual screening query to screen a database of 400,000 virtual molecules and pharmacophore model retrieved 2800 hits. The retrieved hits were subsequently filtered based on the fit value. The selected hits were subjected for docking studies to observe the binding modes of the retrieved hits and also to reduce the false positives. One of the potential hits (thiazole-2-amine derivative) was selected based the pharmacophore fit value, dock score, and synthetic feasibility. A few analogues of the thiazole-2-amine derivative were synthesized. These compounds were screened for FGFR1 activity and anti-proliferative studies. The top active compound showed 56.87% inhibition of FGFR1 activity at 50 µM and also showed good cellular activity. Further optimization of thiazole-2-amine derivatives is in progress.

Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

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

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.

Dynamic coal mine model. [Generic feedback-loop model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, M.S.

1978-01-01

This study examines the determinants of the productive life cycle of a single hypothetical coal mine. The article addresses the questions of how long the mine will operate, what its annual production will be, and what percentage of the resource base will be recovered. As greatly expanded production requires capital investment, the investment decision is singled out as the principal determinant of the mine's dynamic behavior. A simple dynamic feedback loop model was constructed, the performance of which is compared with actual data to see how well the model can reproduce known behavior. Exogenous variables, such as the price ofmore » coal, the wage rate, operating costs, and the tax structure, are then changed to see how these changes affect the mine's performance.« less

Dynamics of internal models in game players

NASA Astrophysics Data System (ADS)

Taiji, Makoto; Ikegami, Takashi

1999-10-01

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

Modeling Quantum Dynamics in Multidimensional Systems

NASA Astrophysics Data System (ADS)

Liss, Kyle; Weinacht, Thomas; Pearson, Brett

2017-04-01

Coupling between different degrees-of-freedom is an inherent aspect of dynamics in multidimensional quantum systems. As experiments and theory begin to tackle larger molecular structures and environments, models that account for vibrational and/or electronic couplings are essential for interpretation. Relevant processes include intramolecular vibrational relaxation, conical intersections, and system-bath coupling. We describe a set of simulations designed to model coupling processes in multidimensional molecular systems, focusing on models that provide insight and allow visualization of the dynamics. Undergraduates carried out much of the work as part of a senior research project. In addition to the pedagogical value, the simulations allow for comparison between both explicit and implicit treatments of a system's many degrees-of-freedom.

Development of a solid propellant viscoelastic dynamic model

NASA Technical Reports Server (NTRS)

Hufferd, W. L.; Fitzgerald, J. E.

1976-01-01

The results of a one year study to develop a dynamic response model for the Space Shuttle Solid Rocket Motor (SRM) propellant are presented. An extensive literature survey was conducted, from which it was concluded that the only significant variables affecting the dynamic response of the SRM propellant are temperature and frequency. Based on this study, and experimental data on propellants related to the SRM propellant, a dynamic constitutive model was developed in the form of a simple power law with temperature incorporated in the form of a modified power law. A computer program was generated which performs a least-squares curve-fit of laboratory data to determine the model parameters and it calculates dynamic moduli at any desired temperature and frequency. Additional studies investigated dynamic scaling laws and the extent of coupling between the SRM propellant and motor cases. It was found, in agreement with other investigations, that the propellant provides all of the mass and damping characteristics whereas the case provides all of the stiffness.

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

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.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

Non-Deterministic Modelling of Food-Web Dynamics

PubMed Central

Planque, Benjamin; Lindstrøm, Ulf; Subbey, Sam

2014-01-01

A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as ‘null models of food-webs’ as originally advocated. PMID:25299245

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

A locomotive-track coupled vertical dynamics model with gear transmissions

NASA Astrophysics Data System (ADS)

Chen, Zaigang; Zhai, Wanming; Wang, Kaiyun

2017-02-01

A gear transmission system is a key element in a locomotive for the transmission of traction or braking forces between the motor and the wheel-rail interface. Its dynamic performance has a direct effect on the operational reliability of the locomotive and its components. This paper proposes a comprehensive locomotive-track coupled vertical dynamics model, in which the locomotive is driven by axle-hung motors. In this coupled dynamics model, the dynamic interactions between the gear transmission system and the other components, e.g. motor and wheelset, are considered based on the detailed analysis of its structural properties and working mechanism. Thus, the mechanical transmission system for power delivery from the motor to the wheelset via gear transmission is coupled with a traditional locomotive-track dynamics system via the wheel-rail contact interface and the gear mesh interface. This developed dynamics model enables investigations of the dynamic performance of the entire dynamics system under the excitations from the wheel-rail contact interface and/or the gear mesh interface. Dynamic interactions are demonstrated by numerical simulations using this dynamics model. The results indicate that both of the excitations from the wheel-rail contact interface and the gear mesh interface have a significant effect on the dynamic responses of the components in this coupled dynamics system.

Dynamic Modelling of Embeddable Piezoceramic Transducers

PubMed Central

Li, Xu; Li, Hongnan; Wang, Zhijie; Song, Gangbing

2017-01-01

Embedded Lead Zirconate Titanate (PZT) transducers have been widely used in research related to monitoring the health status of concrete structures. This paper presents a dynamic model of an embeddable PZT transducer with a waterproof layer and a protecting layer. The proposed model is verified by finite-element method (FEM). Based on the proposed model, the factors influencing the dynamic property of the embeddable PZT transducers, which include the material and thickness of the protecting layer, the material and thickness of the waterproof layer, and the thickness of the PZT, are analyzed. These analyses are further validated by a series of dynamic stress transfer experiments on embeddable PZT transducers. The results show that the excitation frequency can significantly affect the stress transfer of the PZT transducer in terms of both amplitude and signal phase. The natural frequency in the poling direction for the PZT transducer is affected by the material properties and the thickness of the waterproof and protecting layers. The studies in this paper will provide a scientific basis to design embeddable PZT transducers with special functions. PMID:29206150

Quantum-like model of unconscious–conscious dynamics

PubMed Central

Khrennikov, Andrei

2015-01-01

We present a quantum-like model of sensation–perception dynamics (originated in Helmholtz theory of unconscious inference) based on the theory of quantum apparatuses and instruments. We illustrate our approach with the model of bistable perception of a particular ambiguous figure, the Schröder stair. This is a concrete model for unconscious and conscious processing of information and their interaction. The starting point of our quantum-like journey was the observation that perception dynamics is essentially contextual which implies impossibility of (straightforward) embedding of experimental statistical data in the classical (Kolmogorov, 1933) framework of probability theory. This motivates application of nonclassical probabilistic schemes. And the quantum formalism provides a variety of the well-approved and mathematically elegant probabilistic schemes to handle results of measurements. The theory of quantum apparatuses and instruments is the most general quantum scheme describing measurements and it is natural to explore it to model the sensation–perception dynamics. In particular, this theory provides the scheme of indirect quantum measurements which we apply to model unconscious inference leading to transition from sensations to perceptions. PMID:26283979

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.

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may

OISI dynamic end-to-end modeling tool

NASA Astrophysics Data System (ADS)

Kersten, Michael; Weidler, Alexander; Wilhelm, Rainer; Johann, Ulrich A.; Szerdahelyi, Laszlo

2000-07-01

The OISI Dynamic end-to-end modeling tool is tailored to end-to-end modeling and dynamic simulation of Earth- and space-based actively controlled optical instruments such as e.g. optical stellar interferometers. `End-to-end modeling' is meant to denote the feature that the overall model comprises besides optical sub-models also structural, sensor, actuator, controller and disturbance sub-models influencing the optical transmission, so that the system- level instrument performance due to disturbances and active optics can be simulated. This tool has been developed to support performance analysis and prediction as well as control loop design and fine-tuning for OISI, Germany's preparatory program for optical/infrared spaceborne interferometry initiated in 1994 by Dornier Satellitensysteme GmbH in Friedrichshafen.

Dynamic Modelling with "MLE-Energy Dynamic" for Primary School

NASA Astrophysics Data System (ADS)

Giliberti, Enrico; Corni, Federico

During the recent years simulation and modelling are growing instances in science education. In primary school, however, the main use of software is the simulation, due to the lack of modelling software tools specially designed to fit/accomplish the needs of primary education. In particular primary school teachers need to use simulation in a framework that is both consistent and simple enough to be understandable by children [2]. One of the possible area to approach modelling is about the construction of the concept of energy, in particular for what concerns the relations among substance, potential, power [3]. Following the previous initial research results with this approach [2], and with the static version of the software MLE Energy [1], we suggest the design and the experimentation of a dynamic modelling software—MLE dynamic-capable to represent dynamically the relations occurring when two substance-like quantities exchange energy, modifying their potential. By means of this software the user can graphically choose the dependent and independent variables and leave the other parameters fixed. The software has been initially evaluated, during a course of science education with a group of primary school teachers-to-be, to test the ability of the software to improve teachers' way of thinking in terms of substance-like quantities and their effects (graphical representation of the extensive, intensive variables and their mutual relations); moreover, the software has been tested with a group of primary school teachers, asking their opinion about the software didactical relevance in the class work.

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

A family of dynamic models for large-eddy simulation

NASA Technical Reports Server (NTRS)

Carati, D.; Jansen, K.; Lund, T.

1995-01-01

Since its first application, the dynamic procedure has been recognized as an effective means to compute rather than prescribe the unknown coefficients that appear in a subgrid-scale model for Large-Eddy Simulation (LES). The dynamic procedure is usually used to determine the nondimensional coefficient in the Smagorinsky (1963) model. In reality the procedure is quite general and it is not limited to the Smagorinsky model by any theoretical or practical constraints. The purpose of this note is to consider a generalized family of dynamic eddy viscosity models that do not necessarily rely on the local equilibrium assumption built into the Smagorinsky model. By invoking an inertial range assumption, it will be shown that the coefficients in the new models need not be nondimensional. This additional degree of freedom allows the use of models that are scaled on traditionally unknown quantities such as the dissipation rate. In certain cases, the dynamic models with dimensional coefficients are simpler to implement, and allow for a 30% reduction in the number of required filtering operations.

From terrestrial to aquatic fluxes: Integrating stream dynamics within a dynamic global vegetation modeling framework

NASA Astrophysics Data System (ADS)

Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco

2016-04-01

Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.

Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

DOE PAGES

Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

2015-04-01

The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

Global dynamic modeling of a transmission system

NASA Technical Reports Server (NTRS)

Choy, F. K.; Qian, W.

1993-01-01

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

DSGRN: Examining the Dynamics of Families of Logical Models.

PubMed

Cummins, Bree; Gedeon, Tomas; Harker, Shaun; Mischaikow, Konstantin

2018-01-01

We present a computational tool DSGRN for exploring the dynamics of a network by computing summaries of the dynamics of switching models compatible with the network across all parameters. The network can arise directly from a biological problem, or indirectly as the interaction graph of a Boolean model. This tool computes a finite decomposition of parameter space such that for each region, the state transition graph that describes the coarse dynamical behavior of a network is the same. Each of these parameter regions corresponds to a different logical description of the network dynamics. The comparison of dynamics across parameters with experimental data allows the rejection of parameter regimes or entire networks as viable models for representing the underlying regulatory mechanisms. This in turn allows a search through the space of perturbations of a given network for networks that robustly fit the data. These are the first steps toward discovering a network that optimally matches the observed dynamics by searching through the space of networks.

Toward Simplification of Dynamic Subgrid-Scale Models

NASA Technical Reports Server (NTRS)

Pruett, C. David

1997-01-01

We examine the relationship between the filter and the subgrid-scale (SGS) model for large-eddy simulations, in general, and for those with dynamic SGS models, in particular. From a review of the literature, it would appear that many practitioners of LES consider the link between the filter and the model more or less as a formality of little practical effect. In contrast, we will show that the filter and the model are intimately linked, that the Smagorinsky SGS model is appropriate only for filters of first- or second-order, and that the Smagorinsky model is inconsistent with spectral filters. Moreover, the Germano identity is shown to be both problematic and unnecessary for the development of dynamic SGS models. Its use obscures the following fundamental realization: For a suitably chosen filter, the computible resolved turbulent stresses, property scaled, closely approximate the SGS stresses.

Integrating microbial diversity in soil carbon dynamic models parameters

NASA Astrophysics Data System (ADS)

Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie

2015-04-01

Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten

Model based control of dynamic atomic force microscope.

PubMed

Lee, Chibum; Salapaka, Srinivasa M

2015-04-01

A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

Coupled turbulence and aerosol dynamics modeling of vehicle exhaust plumes using the CTAG model

NASA Astrophysics Data System (ADS)

Wang, Yan Jason; Zhang, K. Max

2012-11-01

This paper presents the development and evaluation of an environmental turbulent reacting flow model, the Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model. CTAG is designed to simulate transport and transformation of multiple air pollutants, e.g., from emission sources to ambient background. For the on-road and near-road applications, CTAG explicitly couples the major turbulent mixing processes, i.e., vehicle-induced turbulence (VIT), road-induced turbulence (RIT) and atmospheric boundary layer turbulence with gas-phase chemistry and aerosol dynamics. CTAG's transport model is referred to as CFD-VIT-RIT. This paper presents the evaluation of the CTAG model in simulating the dynamics of individual plumes in the “tailpipe-to-road” stage, i.e., VIT behind a moving van and aerosol dynamics in the wake of a diesel car by comparing the modeling results against the respective field measurements. Combined with sensitivity studies, we analyze the relative roles of VIT, sulfuric acid induced nucleation, condensation of organic compounds and presence of soot-mode particles in capturing the dynamics of exhaust plumes as well as their implications in vehicle emission controls.

Characterizing and modeling the dynamics of online popularity.

PubMed

Ratkiewicz, Jacob; Fortunato, Santo; Flammini, Alessandro; Menczer, Filippo; Vespignani, Alessandro

2010-10-08

Online popularity has an enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.

Activated aging dynamics and effective trap model description in the random energy model

NASA Astrophysics Data System (ADS)

Baity-Jesi, M.; Biroli, G.; Cammarota, C.

2018-01-01

We study the out-of-equilibrium aging dynamics of the random energy model (REM) ruled by a single spin-flip Metropolis dynamics. We focus on the dynamical evolution taking place on time-scales diverging with the system size. Our aim is to show to what extent the activated dynamics displayed by the REM can be described in terms of an effective trap model. We identify two time regimes: the first one corresponds to the process of escaping from a basin in the energy landscape and to the subsequent exploration of high energy configurations, whereas the second one corresponds to the evolution from a deep basin to the other. By combining numerical simulations with analytical arguments we show why the trap model description does not hold in the former but becomes exact in the second.

Indonesia’s Electricity Demand Dynamic Modelling

NASA Astrophysics Data System (ADS)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems

PubMed Central

2016-01-01

Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of “ODEs and formalized flow diagrams” as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler’s behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918

Collisional model for granular impact dynamics.

PubMed

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

2014-01-01

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

Slow dynamics in translation-invariant quantum lattice models

NASA Astrophysics Data System (ADS)

Michailidis, Alexios A.; Žnidarič, Marko; Medvedyeva, Mariya; Abanin, Dmitry A.; Prosen, Tomaž; Papić, Z.

2018-03-01

Many-body quantum systems typically display fast dynamics and ballistic spreading of information. Here we address the open problem of how slow the dynamics can be after a generic breaking of integrability by local interactions. We develop a method based on degenerate perturbation theory that reveals slow dynamical regimes and delocalization processes in general translation invariant models, along with accurate estimates of their delocalization time scales. Our results shed light on the fundamental questions of the robustness of quantum integrable systems and the possibility of many-body localization without disorder. As an example, we construct a large class of one-dimensional lattice models where, despite the absence of asymptotic localization, the transient dynamics is exceptionally slow, i.e., the dynamics is indistinguishable from that of many-body localized systems for the system sizes and time scales accessible in experiments and numerical simulations.

A modified social force model for crowd dynamics

NASA Astrophysics Data System (ADS)

Hassan, Ummi Nurmasyitah; Zainuddin, Zarita; Abu-Sulyman, Ibtesam M.

2017-08-01

The Social Force Model (SFM) is one of the most successful models in microscopic pedestrian studies that is used to study the movement of pedestrians. Many modifications have been done to improvise the SFM by earlier researchers such as the incorporation of a constant respect factor into the self-stopping mechanism. Before the new mechanism is introduced, the researchers found out that a pedestrian will immediately come to a halt if other pedestrians are near to him, which seems to be an unrealistic behavior. Therefore, researchers introduce a self-slowing mechanism to gradually stop a pedestrian when he is approaching other pedestrians. Subsequently, the dynamic respect factor is introduced into the self-slowing mechanism based on the density of the pedestrians to make the model even more realistic. In real life situations, the respect factor of the pedestrians should be dynamic values instead of a constant value. However, when we reproduce the simulation of the dynamic respect factor, we found that the movement of the pedestrians are unrealistic because the pedestrians are lacking perception of the pedestrians in front of him. In this paper, we adopted both dynamic respect factor and dynamic angular parameter, called modified dynamic respect factor, which is dependent on the density of the pedestrians. Simulations are performed in a normal unidirectional walkway to compare the simulated pedestrians' movements produced by both models. The results obtained showed that the modified dynamic respect factor produces more realistic movement of the pedestrians which conform to the real situation. Moreover, we also found that the simulations endow the pedestrian with a self-slowing mechanism and a perception of other pedestrians in front of him.

Adaptive-network models of collective dynamics

NASA Astrophysics Data System (ADS)

Zschaler, G.

2012-09-01

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

Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force.

PubMed

Marshall, Deborah A; Burgos-Liz, Lina; IJzerman, Maarten J; Crown, William; Padula, William V; Wong, Peter K; Pasupathy, Kalyan S; Higashi, Mitchell K; Osgood, Nathaniel D

2015-03-01

In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements. This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. We review criteria for selecting the most suitable method depending on 1) the purpose-type of problem and research questions being investigated, 2) the object-scope of the model, and 3) the method to model the object to achieve the purpose. Finally, we provide guidance for emerging good practices for dynamic simulation modeling in the health sector, covering all aspects, from the engagement of decision makers in the model design through model maintenance and upkeep. We conclude by providing some recommendations about the application of these methods to add value to informed decision making, with an emphasis on stakeholder engagement, starting with the problem definition. Finally, we identify areas in which further methodological development will likely occur given the growing "volume, velocity and variety" and availability of "big data" to provide empirical evidence and techniques