Academic literature on the topic 'Multi-target compound'
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Journal articles on the topic "Multi-target compound"
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Feldmann, Christian, Dimitar Yonchev, and Jürgen Bajorath. "Structured data sets of compounds with multi-target and corresponding single-target activity from biological assays." Future Science OA 7, no. 5 (June 2021): FSO685. http://dx.doi.org/10.2144/fsoa-2020-0209.
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Aim: Providing compound data sets for promiscuity analysis with single-target (ST) and multi-target (MT) activity, taking confirmed inactivity against targets into account. Methodology: Compounds and target annotations are extracted from screening assays. For a given combination of targets, MT and ST compounds are identified, ensuring test data completeness. Exemplary results & data: A total of 1242 MT compounds active against five or more targets and 6629 corresponding ST compounds are characterized, organized and made freely available. Limitations & next steps: Screening campaigns typically cover a smaller target space than compounds from the medicinal chemistry literature and their activity annotations might be of lesser quality. Reported compound groups will be subjected to target set-based promiscuity analysis and predictions.
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Feldmann, Christian, Dimitar Yonchev, and Jürgen Bajorath. "Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning." Biomolecules 10, no. 12 (November 27, 2020): 1605. http://dx.doi.org/10.3390/biom10121605.
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Predicting compounds with single- and multi-target activity and exploring origins of compound specificity and promiscuity is of high interest for chemical biology and drug discovery. We present a large-scale analysis of compound promiscuity including two major components. First, high-confidence datasets of compounds with multi- and corresponding single-target activity were extracted from biological screening data. Positive and negative assay results were taken into account and data completeness was ensured. Second, these datasets were investigated using diagnostic machine learning to systematically distinguish between compounds with multi- and single-target activity. Models built on the basis of chemical structure consistently produced meaningful predictions. These findings provided evidence for the presence of structural features differentiating promiscuous and non-promiscuous compounds. Machine learning under varying conditions using modified datasets revealed a strong influence of nearest neighbor relationship on the predictions. Many multi-target compounds were found to be more similar to other multi-target compounds than single-target compounds and vice versa, which resulted in consistently accurate predictions. The results of our study confirm the presence of structural relationships that differentiate promiscuous and non-promiscuous compounds.
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Qureshi, Shahrukh, Ravina Khandelwal, Maddala Madhavi, Naveesha Khurana, Neha Gupta, Saurav K. Choudhary, Revathy A. Suresh, et al. "A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma." Current Topics in Medicinal Chemistry 21, no. 9 (May 26, 2021): 790–818. http://dx.doi.org/10.2174/1568026621666210119112336.
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Background: Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32). Aim: The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL. Methodology: Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds. Results: MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies. Conclusion: Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.
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Rodríguez-Pérez, Raquel, and Jürgen Bajorath. "Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions." Journal of Computer-Aided Molecular Design 35, no. 3 (February 17, 2021): 285–95. http://dx.doi.org/10.1007/s10822-021-00376-8.
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AbstractMachine learning (ML) enables modeling of quantitative structure–activity relationships (QSAR) and compound potency predictions. Recently, multi-target QSAR models have been gaining increasing attention. Simultaneous compound potency predictions for multiple targets can be carried out using ensembles of independently derived target-based QSAR models or in a more integrated and advanced manner using multi-target deep neural networks (MT-DNNs). Herein, single-target and multi-target ML models were systematically compared on a large scale in compound potency value predictions for 270 human targets. By design, this large-magnitude evaluation has been a special feature of our study. To these ends, MT-DNN, single-target DNN (ST-DNN), support vector regression (SVR), and random forest regression (RFR) models were implemented. Different test systems were defined to benchmark these ML methods under conditions of varying complexity. Source compounds were divided into training and test sets in a compound- or analog series-based manner taking target information into account. Data partitioning approaches used for model training and evaluation were shown to influence the relative performance of ML methods, especially for the most challenging compound data sets. For example, the performance of MT-DNNs with per-target models yielded superior performance compared to single-target models. For a test compound or its analogs, the availability of potency measurements for multiple targets affected model performance, revealing the influence of ML synergies.
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Blaschke, Thomas, and Jürgen Bajorath. "Compound dataset and custom code for deep generative multi-target compound design." Future Science OA 7, no. 6 (July 2021): FSO715. http://dx.doi.org/10.2144/fsoa-2021-0033.
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Aim: Generating a data and software infrastructure for evaluating multi-target compound (MT-CPD) design via deep generative modeling. Methodology: The REINVENT 2.0 approach for generative modeling was extended for MT-CPD design and a large benchmark data set was curated. Exemplary results & data: Proof-of-concept for deep generative MT-CPD design was established. Custom code and the benchmark set comprising 2809 MT-CPDs, 61,928 single-target and 295,395 inactive compounds from biological screens are made freely available. Limitations & next steps: MT-CPD design via deep learning is still at its conceptual stages. It will be required to demonstrate experimental impact. The data and software we provide enable further investigation of MT-CPD design and generation of candidate molecules for experimental programs.
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Knez, Damijan, Izidor Sosič, Anja Pišlar, Ana Mitrović, Marko Jukič, Janko Kos, and Stanislav Gobec. "Biological Evaluation of 8-Hydroxyquinolines as Multi-Target Directed Ligands for Treating Alzheimer’s Disease." Current Alzheimer Research 16, no. 9 (October 29, 2019): 801–14. http://dx.doi.org/10.2174/1567205016666191010130351.
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Background: Accumulating evidence suggests that multi-target directed ligands have great potential for the treatment of complex diseases such as Alzheimer’s Disease (AD). Objective: To evaluate novel chimeric 8-hydroxyquinoline ligands with merged pharmacophores as potential multifunctional ligands for AD. Methods: Nitroxoline, PBT2 and compounds 2-4 were evaluated in-vitro for their inhibitory potencies on cathepsin B, cholinesterases, and monoamine oxidases. Furthermore, chelation, antioxidative properties and the permeability of Blood-Brain Barrier (BBB) were evaluated by spectroscopy-based assays and the inhibition of Amyloid β (Aβ) aggregation was determined in immunoassay. Cell-based assays were performed to determine cytotoxicity, neuroprotection against toxic Aβ species, and the effects of compound 2 on apoptotic cascade. Results: Compounds 2-4 competitively inhibited cathepsin B β-secretase activity, chelated metal ions and were weak antioxidants. All of the compounds inhibited Aβ aggregation, whereas only compound 2 had a good BBB permeability according to the parallel artificial membrane permeability assay. Tested ligands 2 and 3 were not cytotoxic to SH-SY5Y and HepG2 cells at 10 μM. Compound 2 exerted neuroprotective effects towards Aβ toxicity, reduced the activation of caspase-3/7 and diminished the apoptosis of cells treated with Aβ1-42. Conclusion: Taken together, our data suggest that compound 2 holds a promise to be used as a multifunctional ligand for AD.
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Goff, Aaron, Daire Cantillon, Leticia Muraro Wildner, and Simon J. Waddell. "Multi-Omics Technologies Applied to Tuberculosis Drug Discovery." Applied Sciences 10, no. 13 (July 3, 2020): 4629. http://dx.doi.org/10.3390/app10134629.
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Multi-omics strategies are indispensable tools in the search for new anti-tuberculosis drugs. Omics methodologies, where the ensemble of a class of biological molecules are measured and evaluated together, enable drug discovery programs to answer two fundamental questions. Firstly, in a discovery biology approach, to find new targets in druggable pathways for target-based investigation, advancing from target to lead compound. Secondly, in a discovery chemistry approach, to identify the mode of action of lead compounds derived from high-throughput screens, progressing from compound to target. The advantage of multi-omics methodologies in both of these settings is that omics approaches are unsupervised and unbiased to a priori hypotheses, making omics useful tools to confirm drug action, reveal new insights into compound activity, and discover new avenues for inquiry. This review summarizes the application of Mycobacterium tuberculosis omics technologies to the early stages of tuberculosis antimicrobial drug discovery.
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Hu, Ye, Disha Gupta-Ostermann, and Jürgen Bajorath. "EXPLORING COMPOUND PROMISCUITY PATTERNS AND MULTI-TARGET ACTIVITY SPACES." Computational and Structural Biotechnology Journal 9, no. 13 (January 2014): e201401003. http://dx.doi.org/10.5936/csbj.201401003.
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Bieler, Michael, Michael Reutlinger, Tiago Rodrigues, Petra Schneider, Jan M. Kriegl, and Gisbert Schneider. "Designing Multi-target Compound Libraries with Gaussian Process Models." Molecular Informatics 35, no. 5 (March 2, 2016): 192–98. http://dx.doi.org/10.1002/minf.201501012.
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Poliseno, Viviana, Sílvia Chaves, Leonardo Brunetti, Fulvio Loiodice, Antonio Carrieri, Antonio Laghezza, Paolo Tortorella, et al. "Derivatives of Tenuazonic Acid as Potential New Multi-Target Anti-Alzheimer’s Disease Agents." Biomolecules 11, no. 1 (January 15, 2021): 111. http://dx.doi.org/10.3390/biom11010111.
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Alzheimer’s disease (AD) is generally recognized as a multifactorial neurodegenerative pathology with an increasing impact on society. Tenuazonic acid (TA) is a natural compound that was recently identified as a potential multitarget ligand with anti-cholinesterase, anti-amyloidogenic and antioxidant activities. Using its structure as a chemical scaffold, we synthesized and evaluated new derivatives (1–5), including tenuazonic-donepezil (TA-DNP) hybrids (4 and 5) due to the clinical importance of the anti-AD drug donepezil. These novel compounds all achieved activity in the micromolar range towards all selected targets and demonstrated to be potentially orally absorbed. Moreover, a selected compound (1) was further investigated as a chelating agent towards copper (II), zinc (II) and iron (III) and showed good chelating ability (pFe = 16.6, pCu = 11.6, pZn = 6.0 at pH 7.4). Therefore, the TA motif can be considered an interesting building block in the search for innovative multi-functional anti-neurodegenerative drugs, as exemplified by hybrid 5, a promising non-cytotoxic lead compound adequate for the early stages of AD, and capable of ameliorating the oxidative status of SH-SY5Y human neuroblastoma cells.
Dissertations / Theses on the topic "Multi-target compound"
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ARTASENSI, ANGELICA. "REPURPOSING AND MORPHING: A COMBINED STRATEGY TO DESIGN MULTI TARGET LIGANDS." Doctoral thesis, Università degli Studi di Milano, 2022. http://hdl.handle.net/2434/920444.
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Type 2 diabetes mellitus (T2DM) is one of the priority global health problems, which is characterized by dysregulation of carbohydrate, lipid, and protein metabolism and results from impaired insulin secretion, insulin resistance, or a combination of both. The global burden of diabetes had increased significantly since 19901, compelled to face this syndrome not only as a major threat to public health but also to socio-economic development.
The explosion of T2DM prevalence over the past half-century has paralleled that of the obesity epidemic2. The two inflammatory diseases are correlated since it has been shown that obesity induces immune cell changes in adipose tissue that affect insulin sensitivity3,4. Obesity and insulin resistance are two key drivers in the development of T2DM and are also connected to the development of both microvascular complications (including retinopathy, nephropathy, and neuropathy) and macrovascular complications (such as cardiovascular comorbidities). Other notable risk factors include a poor diet, low physical activity levels, and older age.
Multifactorial risk reduction strategies to normalize blood levels, lipid profile, and blood pressure are required to manage T2DM. Furthermore, it is also required continuous medical care, patient self-management for control of abnormal glucose levels.
Achievement of glycemic control requires a pharmacological approach that has progressed from biguanides and metformin to a wide spectrum of medications that seems to provide a beneficial effect on morbidity and mortality. Despite this, the target treatment goals are still not completely reached, so polypharmacological treatment is needed5. However, complex treatment regimens may lead to drug-drug interaction and/or poor patient adherence. Thus, novel antidiabetic drug classes capable of acting on several levels simultaneously are required. Nevertheless, in the state of metabolic disturbance, several major enzymes are abnormally expressed, thus they could be interesting targets in drug development. Hence, again, multimodal drugs, which could reduce hyperglycemia and concomitantly inhibit the progression of complications, may offer a valuable therapeutic option. The design of these multi-target ligands must focus on the selection of suitable targets, which must be well characterized and preferably implicated in different pathways of the disease, and on the optimization of the relative potency of the compound towards each interested protein6. To find new therapeutic compounds, a repurposing approach was applied on WB-4101, a well-known adrenergic ligand, to obtain potential dual ligands that would target different enzymes involved in T2DM, namely Dipeptidyl Peptidase IV (DPP-IV) and Carbonic Anhydrase (CA-II and V).
DPP-IV inhibitors prolong the half-life of the glucose-dependent insulinotropic polypeptide hormone (GIP) and the glucagon-like peptide 1 (GLP-1), two important regulators of post-prandial glycemic control7. On the other hand, CA inhibitors could be useful in the prevention of several common diabetic comorbidities.
WB-4101 has been chosen as a good “repurposable” candidate since previous computational studies showed that it conveniently fits into all these enzymes’ pockets even if fails to interact with some key residues. To strengthen interactions towards the target enzymes, morphing WB-4101 has been required. Furthermore, this approach can lead to the design of more “drug-like” compounds with low molecular weight and with respect to Lipinski's rule of five.
Moreover, morphing would allow the modulation of the activity toward the old and new targets.
References
1. Saeedi, P. et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res. Clin. Pract. 157, (2019).
2. Wang, Y. C., McPherson, K., Marsh, T., Gortmaker, S. L. & Brown, M. Health and economic burden of the projected obesity trends in the USA and the UK. The Lancet vol. 378 815–825 (2011).
3. Weisberg, S. P. et al. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 112, 1796–1808 (2003).
4. Xu, H. et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J. Clin. Invest. 112, 1821–1830 (2003).
5. Artasensi, A., Pedretti, A., Vistoli, G. & Fumagalli, L. Type 2 Diabetes Mellitus: A Review of Multi-Target Drugs. Molecules 25, 1987 (2020).
6. Morphy, R., Kay, C. & Rankovic, Z. From magic bullets to designed multiple ligands. Drug Discov. Today 9, 641–651 (2004).
7. Irwin, N. New perspectives on exploitation of incretin peptides for the treatment of diabetes and related disorders. World J. Diabetes 6, 1285 (2015).
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Di, Pietro Ornella. "Exploring heterocyclic scaffolds in the development of multi-target anti-Alzheimer and multi-trypanosomatid compounds." Doctoral thesis, Universitat de Barcelona, 2015. http://hdl.handle.net/10803/318585.
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The aim of this PhD thesis consists of the synergistic combination of both highly efficient synthetic approaches and molecular modelling tools for the structure-based drug design and synthesis of novel bioactive heterocyclic compounds. The work carried out has followed two main research lines, namely the development of novel disease-modifying anti-Alzheimer agents and still unexplored chemical entities for the treatment of Neglected Tropical Diseases (NTDs). The results obtained have been presented as a compendium of publications and draft manuscripts. In the framework of the anti-Alzheimer research line, first the hit-to-lead optimization of a practically inactive propidium-related compound easily accessed via a Povarov multicomponent reaction (MCR) approach (Di Pietro O. et al. Eur. J. Med. Chem., 2014, 73, 141), and the subsequent molecular hybridization with a 6-chlorotacrine unit through a molecular dynamics-driven tether length optimization, overall led to one of the most potent non-covalent dual binding site acetylcholinesterase inhibitor (AChEI) ever described in the literature (Di Pietro O. et al. Eur. J. Med. Chem., 2014, 84, 107).
Second, the combined recourse to the highly versatile click-chemistry strategy, through the well-known Cu-catalyzed azide-alkyne cycloaddition reaction, and convenient computational chemistry tools, allowed the rational design and synthesis of a novel series of 1,4-disubstituted triazole-based propargylamines as irreversible MAO-B inhibitors (draft manuscript) with the perspective to be further linked to a second pharmacophoric moiety to derive novel MTDLs as potential anti-Alzheimer drug candidates.
Furthermore, an extensive computation of the BACE-1 apo conformational ensemble by means of combined molecular dynamics technique and Principal Component Analysis (PCA) method, allowed to carry out an exhaustive study of a secondary transient druggable pocket (draft manuscript) and a virtual screening of 500,000 commercially available fragments for further drug discovery purposes.
Finally, in the framework of the NTDs research line, 2−4-step sequences involving as the key step an initial Povarov MCR gave easy access to a small library of quinolones and tricyclic heterofused quinolines, which were subjected to phenotypic whole-cell screenings, leading to the individuation of several low micromolar multi-trypanosomatid hit compounds (Di Pietro et al. Eur. J. Med. Chem. 2015, accepted with minor revision).
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Rizzo, Stefano <1979>. "Design and Synthesis of Multi Target Compounds for the Treatment of Alzheimer's Disease." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1751/1/Rizzo_Stefano_Tesi_pdf...pdf.
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Rizzo, Stefano <1979>. "Design and Synthesis of Multi Target Compounds for the Treatment of Alzheimer's Disease." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1751/.
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Dalla, Via Martina. "Development of multifunctional anticancer agents: design, synthesis and evaluation of hybrid compounds containing kinase inhibitor moieties." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421807.
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Cancer is a complex and a multiple-genes involved disease; for this reason it can not be treated or cured with a single drug modulating the biological function of a single target. The innovation related to multi-targeted drugs, combining the activity of different cancer progression relevant targets, became a burgeoning research topic. Drugs that act on multiple targets can enhance efficacy and reduce chemo-resistance that causes disease relapse and metastasis and remains the main obstacle to cancer therapy. One of the main target nowadays are tyrosine kinases (TKs); since most protein kinases stimulate cell growth and proliferation, cell survival and migration, they can, if overexpressed, amplified or constitutively active, assume oncogenic properties. Other ideal biological targets are enzymes as histone deacetylases (HDAC) and mitochondrial functions. Herein we present the development and the preliminary evaluation of new Abl/HDAC inhibitors bearing the pyrido-pyrimidine main scaffold; the functionalization of the most active compounds with metal ions (i.e. Zn2+, Cu2+ and Fe3+); the development of novel multi-kinase inhibitors bearing the 4-anilinopyrimidine scaffold; the development of novel cKIT/wtRET/V804MRET inhibitors bearing the 4-anilinopyridine scaffold. Besides, the development of multi-kinase inhibitors endowed with antifibrotic properties as well as novel topoisomerase inhibitors are reported.Il cancro è una patologia complessa che coinvolge più geni; per questo motivo non può essere trattato o curato con un singolo farmaco che regola l'attività biologica di un unico bersaglio. L'innovazione dei farmaci multi-target, che combinano l'attività contro diversi bersagli coinvolti nella progressione del tumore, è diventato un promettente argomento di ricerca. Farmaci che agiscono su più bersagli possono aumentare l'efficacia della terapia riducendo il fenomeno di resistenza che causa ricadute e metastasi restando uno dei maggiori ostacoli della terapia antitumorale. Le tirosin-chinasi sono considerate ad oggi tra i principali bersagli in quanto molte protein chinasi stimolando la crescita, la proliferazione e la migrazione cellulare e se sovra espresse, amplificate o costitutivamente attivate assumono proprietà oncogeniche. Altri bersagli biologici ideali sono enzimi quali gli istone deacetilasi e le funzioni mitocondriali. Nella tesi sono presentati lo sviluppo e la valutazione biologica preliminare di nuovi inibitori duali di Abl e HDAC caratterizzati da una porzione pirido-pirimidinica; la funzionalizzazione dei composti più attivi con ioni metallici (i.e. Zn2+, Cu2+ and Fe3+); lo sviluppo di nuovi inibitori multi-chinasi caratterizzati da una porzione 4-anilinopirimidinica; lo sviluppo di nuovi inibitori di cKIT/wtRET/V804MRET a struttura 4-anilinopiridinica. Sono inoltre riportati lo sviluppo di nuovi inibitori multichinasici ad attività antifibrotica ed inibitori di topoisomerasi.
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Teponnou, Gerard A. Kenfack. "Tacrine, trolox and tryptoline as lead compounds for the design and synthesis of multi-target drugs for Alzheimer's disease therapy." Thesis, University of the Western Cape, 2016. http://hdl.handle.net/11394/5344.
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Magister Pharmaceuticae - MPharmThe cascade of neurotoxic events involved in the pathogenesis of Alzheimer's disease may explain the inefficacy of currently available treatment based on acetylcholinesterase inhibitors (AChEI - donepezil, galantamine, rivastigmine) and N-methyl-D-aspartate (NMDA) antagonists (memantine). These drugs were designed based on the "one-moleculeone- target" paradigm and only address a single target. Conversely, the multi-target drug design strategy increasingly gains recognition. Based on the versatile biological activities of tacrine, trolox and β-carboline derivatives, the attention they have received as lead structures for the design of multifunctional drugs for the treatment of Alzheimer's disease, and the topology of the active site of AChE, we have designed tacrine-trolox and tacrine-tryptoline hybrids with various linker chain lengths. The aim with these hybrids was to provide additive or synergistic therapeutic effects that might help overcome the limitation of current anti Alzheimer's disease drugs. All synthesized compounds were designed from lead structures (tacrine, tryptoline and trolox) to obtain cholinesterase (ChE) multisite binders and multifunctional AD agents. The study was rationalized by docking all structures in the active site of TcAChE using Molecular Operating Environment (MOE) software before proceeding with the synthesis. ChE inhibition was assessed in a UV enzyme inhibition assay using Ellman's method. Antioxidant activities were assessed using the 2, 2-diphenyl-1-picrylhydrazyl (DPPH.) absorbance assay. The hybrids containing the trolox moiety (compounds 8a-e) showed moderate to high AChE inhibitory activity in the nano to micro molar range (IC₅₀: 17.37 - 2200 nM), BuChE inhibition was observed in the same range (IC₅₀: 3.16 – 128.82 nM), and free radical scavenging activities in micro molar range (IC50: 11.48 – 49.23 µM). These are comparable or slightly higher than their reference compounds donepezil (AChE IC₅₀ = 220 nM), tacrine (BuChE IC₅₀: 14.12 nM), and trolox (DPPH IC₅₀: 17.57 µM). The hybrids with longer linker chain lengths, 6 and 8 carbons (8d and 8e), showed better ChE inhibitory activity than the shorter ones, 2, 3, and 4 carbons (8a-c respectively). This correlates well with literature. Free radical scavenging activities, however, seems not to be significantly affected by varying linker chain lengths. The hybrid compound (14) containing the tryptoline moiety linked with a 7 carbon spacer displayed the best AChE and BuChE inhibitory activity (IC₅₀ = 17.37 and 3.16 nM) but poor free radical scavenging activity. Novel anti-Alzheimer's disease drugs with multi-target neuroprotective activities were thus obtained and hybrid molecules that exhibit good ChE inhibition (8d, 8e and 14) and anti-oxidant (8d and 8e) activity were identified as suitable candidates for further investigation.
National Research Foundation (NRF)
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Mariano, Marica [Verfasser], and Rolf W. [Akademischer Betreuer] Hartmann. "Small multi-target compounds for the treatment of neurodegenerative pathologies like Alzheimer’s disease and glioblastoma / Marica Mariano ; Betreuer: Rolf W. Hartmann." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2017. http://d-nb.info/1135956820/34.
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Aung, Thazin Nwe. "Molecular Mechanisms of Natural Compounds : Compound Kushen Injection (CKI) in Cancer." Thesis, 2019. http://hdl.handle.net/2440/120399.
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Chemotherapy is a treatment that uses cytotoxic drugs to kill rapidly dividing cancer cells. There are many anti-cancer chemotherapeutic drugs used alone or in combination with others to kill cancerous cells, and some of these, are of plant origin. Naturally occurring compounds, such as Taxol, are used in chemotherapy and have very specific, unique, molecular targets. However, according to the World Health Organization (Ekor, 2014), approximately eighty percent of the world’s population depends on natural compounds from traditional medicine and these compounds are widely used in complementary medicine as anti-cancer drugs (Foster et al., 2000). Traditional Chinese medicine (TCM) uses treatments that contain multiple natural compounds, a number of which have been claimed to be of therapeutic benefit to cancer sufferers (Chung et al., 2015). Some TCM preparations have shown anti-cancer, anti-migratory and anti-metastatic properties in laboratory settings (Wang et al., 2009;Pan et al., 2011;Qu et al., 2016). Research suggests that TCM natural compound mixtures might synergistically trigger therapeutic benefits through the action of multiple components affecting multiple regulatory signaling targets (Wang et al., 2008). Compound Kushen injection (CKI) is a TCM anticancer agent which has been approved by the Chinese State Food and Drug Administration to treat solid tumors in combination with chemotherapy drugs in clinics for pain relief, cancer metastasis and enhancement of the immune system since 1995, and is used to treat approximately 30,000 patients daily. Although a large body of evidence has suggested CKI has anti-cancer properties (Xu et al., 2011;Gao et al., 2018) the anti-cancer mechanisms attributable to specific compounds within the mixture remain unknown. CKI contains multiple alkaloid and flavonoid compounds and the main bioactive compounds such as matrine and oxymatrine have shown to affect cancer cells in the lab. However, other medicinal herbs containing these two compounds as main components have demonstrated patient toxicity. It is therefore important to better understand the effects of CKI, particularly with respect the contributions of individual compounds within the mixture. In this thesis, I describe a multi-disciplinary approach including analytical chemistry, cellular assays and transcriptome analysis to explore the effects of several major compounds present in CKI. Through the application of a subtractive fractionation method that removed individual compounds one, two or three at a time, I have been able to map these compounds and their interactions to specific pathways based on altered gene expression profiles. This has illuminated the roles of several major compounds of CKI, that on their own, have no, or minimal, activity in our bioassay. This approach has enabled us to identify the interactions between compounds in a mixture as shown by the response of cancer cell cultures. Using a systems biology approach along with cellular migration and invasion assays, I have mapped the activity of related proteins and pathways which may contribute to the migrastatic activity of CKI. Altogether, this thesis presents an initial characterization of the underlying mechanistic changes induced by CKI. First, by comparing differentially expressed genes across treatment combinations generated using our subtractive fractionation approach, I identified specific candidate pathways that were altered by the removal of compounds from the mixture. Second, by using transcriptome data of a breast cancer cell line, the effects of CKI on candidate anti-migratory pathways for six different cancer cell lines were assessed. These experiments identified specific candidate target pathways through which CKI might act. These approaches can be used to understand the roles and interactions of individual compounds from any complex natural compound mixture whose biological activity cannot be associated with purified compounds.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 2019
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Łozińska, Iwona. "Synteza i badania biologiczne nowych inhibitorów cholinoesteraz zawierających ugrupowanie serotoniny i wybranych pochodnych heterocyklicznych." Doctoral thesis, 2016. https://depotuw.ceon.pl/handle/item/1630.
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Projektowanie nowych inhibitorów cholinoesteraz jest bardzo istotnym elementem
poszukiwania leków w chorobie Alzheimera. Wśród obecnie stosowanych farmaceutyków
w terapii tej choroby znajduje się m.in. takryna i donepezil, odwracalne inhibitory
cholinoesteraz – acetylocholinoesterazy (AChE) oraz butyrylocholinowesterazy (BChE),
których pochodne stały się elementami budulcowymi do otrzymania inhibitorów, objętych
rozprawą doktorską.
Etiologia choroby Alzheimera nie jest jeszcze poznana, natomiast wiadomym jest, iż
jest to choroba wieloczynnikowa, w leczeniu której działanie na pojedynczy cel nie
wystarczy. Obecnie trwają prace nad cząsteczką łączącą w swojej strukturze grupy
farmakoforowe różnych leków, a związki te nazywane są MTLDs (multi-target- directed
ligands), czyli lekami wielocelowymi. Leki wielocelowe działają kompleksowo dlatego,
że uwzględniają złożoność molekularnego mechanizmu choroby i dają większe szanse na
wyleczenie pacjenta oraz powstrzymanie procesu chorobowego. Dodatkowo dokładne
poznanie struktury AChE pozwoliło na uzyskanie bardzo cennej wskazówki w projektowaniu
inhibitorów tego enzymu – potencjalny kandydat ma możliwość związania się z AChE
w dwóch miejscach aktywnych (miejscu katalitycznym oraz peryferyjnym). Leki hybrydowe,
dzięki zastosowaniu odpowiedniej długości łańcucha alkilowego pomiędzy grupami
farmakoforowymi, mogą wiązać się z enzymem w dwóch miejscach aktywnych enzymu.
Wychodząc naprzeciw współczesnym oczekiwaniom, moim celem syntetycznym były
molekuły łączące w swojej strukturze inhibitor cholinoesteraz (takryna, donepezil)
oraz pochodną serotoniny (ważnego neuroprzekaźnika 5-HT; 5-hydroksytryptaminy),
wykazującej działanie antydepresyjne, antyoksydacyjne, regulujące zaburzenia
neuroprzekaźnictwa. Elementy budulcowe połączone zostały wiązaniem karbaminianowym,
które trwalej łączy się z cholinoesterazą, niż naturalnie hydrolizowany w acetylocholinie
ester. Otrzymane w ten sposób pochodne, wpisujące się w koncepcję leków wielocelowych,
mogą pełnić wielorakie funkcje.
Zsyntetyzowane heterodimery poddałam następnie badaniom biologicznym in vitro,
w celu określenia ich aktywności pod kątem inhibicji cholinoesteraz metodą Ellmana. Metoda
opiera się na kolorymetrycznym pomiarze produktu reakcji hydrolizy tioacetylocholiny
(ASCh), bądź tiobutyrylocholiny (BSCh) z odczynnikiem Ellmana. W badanej próbce
znajduje się ASCh/BSCh, AChE/BChE (pozyskana z krwi ludzkiej), inhibitor oraz odczynnik
Ellmana. Stopień zabarwienia, zmierzony za pomocą spektroskopu UV-Vis, świadczy
o stopniu zajścia hydrolizy, ta zaś o stopniu inhibicji. Wyniki badań biologicznych wyraża się
za pomocą indeksu IC 50 (ang. half maximal inhibitory concentration), który określa stężenie
inhibitora, powodujące 50%-ową inhibicję enzymu – AChE bądź BChE. Otrzymane związki
okazały się być bardzo aktywnymi oraz selektywnymi inhibitorami, co oznacza, że są
potencjalnymi farmaceutykami w terapii choroby Alzheimera.
Pośród gamy otrzymanych i przebadanych biologicznie związków objętych pracą (14
nowych, nie znanych dotąd w literaturze heterodimerów) można wyróżnić zarówno
selektywne inhibitory AChE jak i BChE. W większości są to jednak bardzo aktywne,
selektywne inhibitory względem BChE, jest to bardzo istotne, gdyż najnowsze doniesienia
naukowe sugerują, iż znacznie lepsze efekty terapeutyczne przynosi strategia ukierunkowana
na hamowanie BChE, wysoka selektywność względem BChE jest zatem dużym atutem.
Na podstawie szeregu badań udało się określić optymalną długość łańcucha węglowego,
pełniącego funkcję linkera oraz wyłonić najbardziej aktywne heterodimery, Na uwagę
zasługuje heretodimer nawet 400 razy bardziej aktywny niż takryna, którego wartość IC 50
wyrażana jest w dziesiątej części nM., związek 2600 razy bardziej aktywny niż donepezil
oraz najbardziej aktywny względem BChE inhibitor, którego wartość IC 50 wynosi 0,24 nM,
czyli 240 pM. Wynik ten należy zaliczyć do jednych z najlepszych, jakie zostały dotąd
opisane w literaturze dla inhibitorów butyrylocholinoesterazy.
Heterodimery które okazały się być bardzo aktywne, zostały zatem objęte ochroną
patentową, numer zgłoszenia to PCT/PL2012/000038.The aim of my research was to synthesize new hybrid cholinesterase inhibitors, which combine different heterocyclic fragments - tacrine or donepezil (today’s pharmaceutics in Alzheimer disease, cholinesterase inhibitors) and serotonin (5-hydroxytryptamine 5-THA, neurotransmitter) which should act in the hybrid molecule as a regulator of neurotransmission, antioxidant and antidepressant, linked by the carbamate bond (which proved essential for bioactivity). Wide range of synthesized compounds differ in the length of the carbon chain and in a kind and location of substituents. The last step was to evaluate in vitro the biological activity of the novel heterodimers toward cholinesterase inhibition using Ellman’s method. Design of new inhibitors of cholinesterases is a very important part of drug discovery for Alzheimer's disease (AD). The etiology of the disease is not yet fully understood, but it is known that AD has multifactorial origin and it’s not surprising that the current drug design paradigm of one-drug-one-target may not be a sufficient model to develop treatment regiments for AD. Medicinal research is constantly seeking for improvement of the efficiency of drugs. The newest strategy is to combine in one molecule pharmacophores of different drugs in the same structure to afford hybrid molecules. The MTLDs (multi-target-directed ligands), hybrid drugs incorporate two drug pharmacophores in one single molecule with the intention to exert dual drug action. After coupling, the molecule acquires better properties. For example, the inhibitor’s activity increases (synergic effect) and it can connect with different parts of the enzyme (peripheral and active binding sites). Thus obtained derivatives may serve multiple functions, not only inhibiting the progression of the disease, but also targeting other symptoms. Synthesized hybrids show that such coupling results in higher biological activity. Several compounds were proven highly active and selective inhibitors of cholinoesterases. Those compounds are covered by a pending patent and constitute an invention reported to the Patent Office of RP - Pat. Appl. No. PCT/PL2012/000038. The study of biological activity were measured in cooperation with Medical Centre of Postgraduate Education in Warsaw. Analysis is performed according to the Ellman method. This method of evaluation of the activity of cholinesterase inhibitors is based on the fact that AChE/BChE interacts with the inhibitor, thus preventing the acetyl/ butyrylcholine hydrolysis. The inhibitor diminishes the enzyme activity which is dependent on the inhibitor concentration. The enzyme unbound to the inhibitor is still able to hydrolyze acetyl/butyrylthiocholine (ASCh/BSCh). The amount of the hydrolyzed ASCh/BSCh is measured indirectly, by quantification of the product of its reaction with DTNB (5,5′-dithio-bis-2-nitrobenzoic acid). Ellman’s method relies therefore on the spectrophotometric quantification of the product of the reaction between acylthiocholine and DTNB. Samples of AChE and BChE were derived from human whole red blood cells and plasma, respectively, according to the known procedure. The enzyme activity at each concentration of the tested compound was expressed as a percent of the activity in the absence of the compound and plotted as a function of its log concentration. The inhibitory activity was calculated as IC50 value. IC50 value corresponds to the inhibitor concentration which causes a 50% decrease in the enzyme activity. The collected data are very promising and interesting, new compounds are more selective inhibitors of BChE, which is particularly important, since high selectivity toward BChE is a demanded value nowadays. Obtained hybrids are even 2600 times more active than donepezil and even 400 times more active than tacrine.
Book chapters on the topic "Multi-target compound"
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Chen, Yaqi, Zhui Chen, and Yi Wang. "Immobilized Magnetic Beads-Based Multi-Target Affinity Selection Coupled with HPLC-MS for Screening Active Compounds from Traditional Chinese Medicine and Natural Products." In Methods in Molecular Biology, 121–29. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2447-9_11.
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Hikmawati, D., T. Respati, Y. Yuniarti, and L. Yuniarti. "In silico analysis of multi-target antimelasma aloe vera compound." In Medical Technology and Environmental Health, 136–40. CRC Press, 2020. http://dx.doi.org/10.1201/9781003016700-24.
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Kumari, Archana, and Rajesh K. Singh. "Morpholine: Pharmacophore Modulating Pharmacokinetic Properties of Anticancer Leads." In Key Heterocyclic Cores for Smart Anticancer Drug–Design Part II, 137–73. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/9789815040043122020008.
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The morpholine ring is considered the most preferred and versatile heterocylic ring in medicinal chemistry due to its distinctive mechanistic activities that give it various biological activities. The eminence of the morpholine ring to modulate the pharmacokinetic properties of the compound, further makes it a fundamental pharmacophore in developing lead molecules. Multi-drug resistance in cancer leads to discovering selective and potent chemotherapeutic agents. Researchers are designing and synthesizing morpholine derivatives as potential anticancer drugs those act by targeting various signaling pathways driven by various protein kinases in the cell, i.e. Ras-Raf-MEK-ERK (ERK) and PI3K/Akt/mTOR, thereby inhibiting cell proliferation and growth. The potency of natural and synthetic derivatives of morpholine makes it a drug of choice for cancer treatment. Many of the morpholine containing anticancer drugs are under clinical trials. Hence, morpholine ring synthesis also becomes a central target for various scientists using green synthesis by straightforward one-step methods. A substantial literature is available on synthetic techniques of morpholine and substituted morpholine. The present chapter updates diverse new synthetic strategies of the morpholine ring and morpholine derivatives with potent anticancer activity. The chapter will also highlight the clinical data of morpholine derivatives with anticancer activity and mechanism of action. The latest information on novel anticancer morpholine derivatives with structural activity relationship (SAR) is also included. This chapter provides information about the necessary structural modifications required in drugs' chemical structure and contribute to the anticancer drug discovery program.
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Jianmongkol, Suree. "Overcoming P-Glycoprotein-Mediated Doxorubicin Resistance." In Advances in Precision Medicine Oncology. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.95553.
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Intracellular concentration of doxorubicin in target cancer cells is a major determinant of therapeutic success of doxorubicin-based regimens. As known, doxorubicin is a substrate of P-glycoprotein (P-gp), the drug efflux transporter in the ABC superfamily. High expression level of P-gp in cancer cells can prevent intracellular accumulation of doxorubicin up to its effective level, leading to doxorubicin resistance and treatment failure. Moreover, these P-gp-overexpressed cells display multi-drug resistance (MDR) phenotype. Regarding this, application of P-gp modulators (suppressor of P-gp activity and expression) is likely to reverse MDR and restore cell sensitivity to doxorubicin treatment. In searching for potential chemo-sensitizer against resistant cancer, a number of phytochemicals or dietary compounds have been studied extensively for their P-gp modulating effects. Furthermore, combination between doxorubicin and P-gp modulators (e.g., plant-derived compounds, siRNA) given through specific target delivery platforms have been an effective strategic approach for MDR reversal and restore doxorubicin effectiveness for cancer treatment.
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Romário da Silva, Diego, Tahyná Duda Deps, Otavio Akira Souza Sakaguchi, Edja Maria Melo de Brito Costa, Carlus Alberto Oliveira dos Santos, Joanilda Paolla Raimundo e Silva, Bruna Dantas da Silva, Frederico Favaro Ribeiro, Francisco Jaime Bezerra Mendonça-Júnior, and Andréa Cristina Barbosa da Silva. "Molecular Docking of Phytochemicals against Streptococcus mutans Virulence Targets: A Proteomic Insight into Drug Planning." In Oral Health Care [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101506.
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Streptococcus mutans (S. mutans) is the most prevalent and most associated with dental caries. Here we aim to identify, through an in silico study, potential bioactive molecules against S. mutans. Twenty-four bioactive molecules with proven action against S. mutans were selected: 1-methoxyficifolinol; 5,7,2′,4′-tetrahydroxy-8-lavandulylflavanone (sophoraflavanone G); 6,8-diprenylgenistein; apigenin; artocarpesin; artocarpin; darbergioidin; dihydrobiochanin A; dihydrocajanin (5,2′,4′-trihydroxy-7-methoxyisoflavanone); erycristagallin; Erystagallin; ferreirin; fisetin; kaempferol; licoricidin; licorisoflavan A; licorisoflavan C; licorisoflavan E; luteolin (3′,4′,5,7-tetrahydroxyflavone); malvidin-3,5-diglucoside; myricetin; orientanol B; quercetin; and quercitrin. Moreover, we selected nine important target proteins for the virulence of this microorganism to perform as drug targets: antigen I/II (region V) (PDB: 1JMM); Antigen I/II (carbox-terminal region) (PDB: 3QE5); Spap (PDB: 3OPU); UA159sp signaling peptide (PDB: 2I2J); TCP3 signaling peptide (PDB: 2I2H); ATP-binding protein ComA (PDB: 3VX4); glucanosucrase (PDB: 3AIC); dextranase (PDB: 3VMO), and Hemolysin (PDB: 2RK5). Five molecules were revealed to be the best ligands for at least three target proteins, highlighting the following compounds: 11 (erystagallin), 10 (erycristagallin), 1 (methoxyficifonilol), 20 (malvidin-3,5-diglucoside), and 2 (sophoraflavanone G), which indicates a possible multi-target action of these compounds. Therefore, based on these findings, in vitro and in vivo tests should be performed to validate the effectiveness of these compounds in inhibiting S. mutans virulence factors. Furthermore, the promising results of these assays will allow the incorporation of these phytoconstituents in products for oral use for the control of tooth decay.
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Sebhatu, Siraj, Pooja, and Parmd Nand. "Intelligent System for Diagnosis of Pulmonary Tuberculosis using Machine Learning." In Cyber Crime, Regulations and Security - Contemporary Issues and Challenges, 277–98. Law brigade publishers, 2022. http://dx.doi.org/10.55662/book.2022ccrs.017.
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In this research, model development is carried out under supervised learning, as the system tries to correct and update itself by comparing the outcome with the target result. After all, only one model category is used, enhanced model performance through substituting the selected features with high sensitivity and low accuracy in clinical knowledge. The experimental analysis shows that the Gradient Boosting (GB) XG Boosting model achieves the best result using the original data set to predict PTB-disease. The ensemble model composed of the Adaboost, Bagging, Random Forest, GB, and Multi-Layer Perceptron models is the best to detect. The Ensemble model reaches 97.8 % accuracy, which exceeds each classification’s accuracy. The model is used to help doctors analyze & evaluate medical cases to validate the diagnosis and minimize human error. It effectively mitigates clinical diagnosis in such difficult challenges as microscopic scanning and reduces the likelihood of misdiagnosis. The model differentiates the patient using a voting method of different machine learning classifiers to provide accurate solutions from having only one model. The novelty of this approach lies in its adaptability to the ensemble model that is continually optimizing itself based on data.
Conference papers on the topic "Multi-target compound"
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Shi, Rui, Rui Xu, Hongjie Wang, Xin Wang, Di Wu, and Zhuo Li. "Multi-point sources and imaging compound infrared target simulator." In International Symposium on Optoelectronic Technology and Application 2014, edited by Mircea Guina, Haimei Gong, Zhichuan Niu, and Jin Lu. SPIE, 2014. http://dx.doi.org/10.1117/12.2072463.
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Stępnicki, Piotr, Katarzyna Targowska-Duda, Andrea Silva, Oliwia Koszła, Ewa Kędzierska, Angelika Grudzińska, Marta Kruk-Słomka, Grażyna Biała, Marián Castro, and Agnieszka Kaczor. "Structural and biological evaluation of novel multi-target compound with potential application in the treatment of schizophrenia." In 1st International Electronic Conference on Biomedicine. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/ecb2021-10263.
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Liu, Yang, Lingyu Sun, Lijun Li, Yiben Zhang, Zongmiao Dai, and Zhenkai Xiong. "Image Identification of a Moving Object Based on an Improved Canny Edge Detection Algorithm." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86792.
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Edge detection plays an increasingly critical role in image process community, especially for moving object identification problems. For this case, the target object can be captured straightly via the edges beside which there is an obvious jump of grey value or texture. Nowadays, Canny operator has gained great popularity as it shows higher anti-noise performance and presents better detection accuracy in comparison with other edge detection operators like Robert’s, Sobel’s, Prewitt’s etc. However, the Gaussian filter associated with the classic Canny operator is sometimes too simple to decrease the all-type-noise. Additionally, in order to enhance the detection accuracy and lower the pseudo-edges detection ratio, two thresholds, high and low, are chosen artificially which have actually limited the adaptability of the algorithm. In this work, a compound filter, Gaussian-Median filter, is proposed to improve the smoothing effect. The self-adaptive multi-threshold Otsu algorithm is realized to determine the high/low threshold automatically according to the grey value statistic. Image moment method is conducted on basis of the detected moving object edges to locate the centroid and to compute the principal orientation. The experimental results based upon locating the edges of both static and moving objects proved the good robustness and the excellent accuracy of the proposed method.
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Takahashi, Toshihiko, Kazunori Watanabe, Tomoharu Fujii, and Terutaka Fujioka. "Numerical Analysis of Temperature Distribution of a Film-Cooled and TBC Coated Blade." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50730.
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In order to contribute to assessment of structural integrity of a gas turbine cooled-blade, numerical estimation of temperature distributions of the blade was conducted. Steady-state simulations by means of one-way coupling of a CFD calculation with thermal conduction analysis were developed and executed to estimate the temperature distributions with using a realistic blade model. Thermal protection schemes applied to the target blade analyzed are external surface film cooling, internal convective cooling and thermal barrier coating (TBC). Non-conformal multi-block meshes were adopted in the analyses for the purpose of reducing turnarounds required in the simulations of real blades, so as to cope with a compound domain including film-cooling holes of various directions. The CFD was applied to flow fields inside and outside of the blade in order to estimate thermal loads imposed on the blade. The temperature distribution of the blade was calculated with the thermal conduction analysis under the conditions based on the CFD calculation. The calculated temperature profiles are in reasonable agreement with local temperature which was estimated on the basis of micro-structural observations of an ex-service blade. The present calculations can also predict influence of lower internal cooling performance on the temperature distribution of the blade.
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Guan, Weilin, and Edwin A. Peraza Hernandez. "Design Framework for Multi-Section Shape Memory Alloy Axial Actuators Considering Material and Geometric Uncertainties." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22683.
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Abstract Shape memory alloys are metallic materials with the capability of performing as high energy density actuators driven by temperature control. This paper presents a design framework for shape memory alloy (SMA) axial actuators composed of multiple wire sections connected in series. The various wire sections forming the actuators can have distinct cross-sectional areas and lengths, which can be modulated to adjust the overall thermomechanical response of the actuator. The design framework aims to find the optimal cross-sectional areas and lengths of the wire sections forming the axial actuator such that its displacement vs. temperature actuation path approximates a target path. Constraints on the length-to-diameter aspect ratio and stress of the wire sections are incorporated. A reduced-order numerical model for the multi-section SMA actuators that allows for efficient design evaluations is derived and implemented. An approach to incorporate uncertainty in the geometry and material parameters of the actuators within the design framework is implemented to allow for the determination of robust actuator designs. A representative application example of the design framework is provided illustrating the benefits of using multiple wire sections in axial actuators to modulate their overall response and approximate a target displacement vs. temperature actuation path.
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Del Barrio, Iker Landa, Julen Cestero, Marco Quartulli, Igor G. Olaizola, Naiara Aginako, and Juan José Ugartemendia. "Using Multi-Physics Simulation to Estimate Energy Flexibility for Local Demand Response Strategies in a Microgrid." In American Modelica Conference 2022, Dallas, October 26-28. Linköping University Electronic Press, 2023. http://dx.doi.org/10.3384/ecp2118675.
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This work discusses the development of a multi-physics simulated model, in the frame of the decarbonization and energy efficiency objectives of the European Commission. Its central feature is the interconnection, through a microgrid, of a distributed PV installation and of several electric dispatchable loads, thus powering a Collective Self-Consumption network. The simulator presented within this document aims to serve as a technological enabler for the design and testing of On-Site DR strategies, which actuate directly on the connection status of the loads, before their deployment on the target, real-world systems. The simulator supports the design and validation of such strategies by generating realistic simulated data of certain loads that present monitoring difficulties, taking into account online, real external weather conditions. All the elements described and modeled in the current work belong to a real-world installation, which is a university campus—ESTIA, Bidart, France— composed by several buildings with DER.
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Wu, Haoyu, Shaomin Xiong, and Toshiki Hirano. "A Real-Time Human Recognition and Tracking System With a Dual-Camera Setup." In ASME 2019 28th Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/isps2019-7469.
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Abstract Most surveillance camera systems are still controlled and monitored by humans. Smart surveillance camera systems are proposed to automatically understand the scene captured, identify the objects of interest, detect the abnormality, etc. However, most surveillance cameras are either wide-angle or pan-tilt-zoom (PTZ). When the cameras are in the wide-view mode, small objects can be hard to be recognized. On the other hand, when the cameras are zoomed-in to the object of interest, the global view cannot be covered and important events outside the zoomed view will be missed. In this paper, we proposed a system composed of a wide-angle camera and a PTZ camera. The system is able to capture the wide-view and the zoomed-view at the same time, taking the advantages from both views. A real-time human detection and identification algorithm based on a neural network is developed. The system can efficiently and effectively recognize humans, distinguish different identities, and follow the person of interest using the PTZ camera. A multi-target multi-camera (MTMC) system is developed based on the original system. In the MTMC system, multiple cameras are placed at different places to look at different views. The same person shown in any camera can be recognized as the same person while different persons can be distinguished among all the cameras.
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Zhang, Yanxin X., and Guogang G. Mu. "Cascaded model of neural networks: a new approach to pattern recognition." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.mbb3.
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The cascaded model of neural networks proposed in this paper is a new approach to pattern recognition. The motivation comes mainly from the fact that the human brain is functionally subdivided into smaller parts. The model consists of some subnets that are functionally complementary and hierarchical, and therefore can enhance the performance of the entire system. Furthermore, the learning process of the cascaded model is carried out separately in each subnet, where the learning rule is much simpler. Therefore, the difficulty of subjecting the model to convergence on a local minimum, as is often the case in multi-layered neural networks, can be avoided. The design of a cascaded system is somewhat similar to that of an optical or electronic system composed of cascaded components. As an example, a 3-D target classifier for four kinds of aircraft with arbitrary spatial orientation is demonstrated based on the cascaded model. Computer simulation and experimental results have shown the model can correctly classify input patterns, both inside and outside the training sets, with rotational invariance.
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Nguyen, Van, Philipp Obermeier, Tran Cao Son, Torsten Schaub, and William Yeoh. "Generalized Target Assignment and Path Finding Using Answer Set Programming." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/169.
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In Multi-Agent Path Finding (MAPF), a team of agents needs to find collision-free paths from their starting locations to their respective targets. Combined Target Assignment and Path Finding (TAPF) extends MAPF by including the problem of assigning targets to agents as a precursor to the MAPF problem. A limitation of both models is their assumption that the number of agents and targets are equal, which is invalid in some applications such as autonomous warehouse systems. We address this limitation by generalizing TAPF to allow for (1)~unequal number of agents and tasks; (2)~tasks to have deadlines by which they must be completed; (3)~ordering of groups of tasks to be completed; and (4)~tasks that are composed of a sequence of checkpoints that must be visited in a specific order. Further, we model the problem using answer set programming (ASP) to show that customizing the desired variant of the problem is simple one only needs to choose the appropriate combination of ASP rules to enforce it. We also demonstrate experimentally that if problem specific information can be incorporated into the ASP encoding then ASP based method can be efficient and can scale up to solve practical applications.
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Boren, Richard M., Charles F. Hammel, and Mark R. Bleckinger. "Multi-Pollution Removal System Using Oxides of Manganese." In ASME 2004 Power Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/power2004-52081.
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Pending legislation suggests there will be a need for increased removal of NOx, SO2, Hg (Mercury) and PM 2.5 from coal-fired power plants. Current commercial technologies only handle one of these pollutants so several different technologies must be combined to remove all of these pollutants. The Pahlman™ Process developed by Enviroscrub Technologies removes NOx, SO2 and Hg in one step. The Pahlman™ Process is a sorbent-based technology, which utilizes a proprietary Oxides of Manganese compound to remove SO2, NOx and Hg. The sorbent is spray-dried into the exhaust duct downstream of the current particulate control device. Spray drying is used to control the particle size (40 micron mean) and increases the surface area of the particle (∼300 m2 /gram). The sorbent is collected in a fabric filter baghouse, which serves two purposes: (1) it captures the entrained sorbent and (2) provides additional residence time for gas-solid contact between the sorbent and the target pollutants. The loaded sorbent is removed from the baghouse and routed to regeneration. Sorbent regeneration occurs in an aqueous solution under temperature and pressure while the solution is maintained in the proper pH and Eh ranges. The reacted manganese is oxidized back to its starting state and sulfate and nitrate byproduct compounds are produced. The insoluble oxides of manganese are then filtered out of the solution and returned to the spray-dryer for re-use. The soluble sulfate and nitrate compounds are separated and the nitrate by-products are sold as fertilizer. The sulfates are further processed and re-used in the regeneration process with excess sulfate by-products sold as fertilizer or used to produce sulfuric acid. Testing over the last three years has resulted in consistent SO2 removal of over 99% and NOx removal of greater than 95%. Testing performed in June 2003 at DTE Energy’s River Rouge Power Station Unit#3 in Detroit, Michigan showed removal rates of >99% for SO2, >98% for NOx and 97% for oxidized Mercury (Hg2+). Mercury testing was performed by the Energy and Environmental Research Center (EERC) and paid for by DTE Energy and the DOE. Testing performed in December 2003 through January 2004 at Minnesota Power’s Boswell Energy Center Unit#4 in Cohasset, Minnesota showed removal rates of >98% for SO2, >94% for NOx and 99.2% for elemental (Hg0) and 94% for total Mercury (HgT).
Reports on the topic "Multi-target compound"
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Beck, Aaron. RiverOceanPlastic: Land-ocean transfer of plastic debris in the North Atlantic, Cruise No. AL534/2, 05 March – 26 March 2020, Malaga (Spain) – Kiel (Germany). GEOMAR Helmholtz Centre for Ocean Research Kiel, 2020. http://dx.doi.org/10.3289/cr_al534-2.
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Cruise AL534/2 is part of a multi-disciplinary research initiative as part of the JPI Oceans project HOTMIC and sought to investigate the origin, transport and fate of plastic debris from estuaries to the oceanic garbage patches. The main focus of the cruise was on the horizontal transfer of plastic debris from major European rivers into shelf regions and on the processes that mediate this transport. Stations were originally chosen to target the outflows of major European rivers along the western Europe coast between Malaga (Spain) and Kiel (Germany), although some modifications were made in response to inclement weather. In total, 16 stations were sampled along the cruise track. The sampling scheme was similar for most stations, and included: 1) a CTD cast to collect water column salinity and temperature profiles, and discrete samples between surface and seafloor, 2) sediment sampling with Van Veen grab and mini-multi corer (mini-MUC), 3) suspended particle and plankton sampling using a towed Bongo net and vertical WP3 net, and 4) surface neusten sampling using a catamaran trawl. At a subset of stations with deep water, suspended particles were collected using in situ pumps deployed on a cable. During transit between stations, surface water samples were collected from the ship’s underway seawater supply, and during calm weather, floating litter was counted by visual survey teams. The samples and data collected on cruise AL534/2 will be used to determine the: (1) abundance of plastic debris in surface waters, as well as the composition of polymer types, originating in major European estuaries and transported through coastal waters, (2) abundance and composition of microplastics (MP) in the water column at different depths from the sea surface to the seafloor including the sediment, (3) abundance and composition of plastic debris in pelagic and benthic organisms (invertebrates), (4) abundance and identity of biofoulers (bacteria, protozoans and metazoans) on the surface of plastic debris from different water depths, (5) identification of chemical compounds (“additives”) in the plastic debris and in water samples.