Relevant bibliographies by topics / Polypharmacological

Academic literature on the topic 'Polypharmacological'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Polypharmacological"

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Garcia-Romero, Ezra Michelet, Edgar López-López, Catalina Soriano-Correa, José L. Medina-Franco, and Carolina Barrientos-Salcedo. "Polypharmacological drug design opportunities against Parkinson's disease." F1000Research 11 (October 17, 2022): 1176. http://dx.doi.org/10.12688/f1000research.124160.1.

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Background: Parkinson's disease is an attractive disease model to extend research towards a better understanding of the interrelationship between genes and the environment (exposome) therefore is an ideal model for a polypharmacological approach due to its clinical heterogeneity. Methods: In this paper, we present a series of polypharmacological chemical scaffolds extracted from ChEMBL 30 Database, with two or more targets of PD-related proteins obtained through chemoinformatics methods. This way, we describe the first adaptation of the Dual Activity Difference (DAD) map that allows the direct identification of "dual activity cliffs". Results: We identified 25 antiparkinson small molecules whose pharmacological targets are directed to dopaminergic and muscarinic acetyl choline M1-M5 receptors; 2 small molecules with three pharmacological targets with norepinephrine transporter, dopaminergic D1-D2 and muscarinic acetyl choline M1-M5 receptors; 6 with both targets norepinephrine transporter and muscarinic acetyl choline M1-M5 receptors; 2 small molecules with norepinephrine transporter and muscarinic acetyl choline M1-M5 receptors and 1 with both adenosine A2a and Dopamine D1-D5 receptors. Conclusion: Chemoinformatics methods identified 36 polypharmacological chemical scaffolds related to Parkinson's disease. Demonstrating that the design of polypharmacological drugs is an opportunity in PD.
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Peragovics, Agnes, Zoltan Simon, Andras Malnasi-Csizmadia, and Andreas Bender. "Modeling Polypharmacological Profiles by Affinity Fingerprinting." Current Pharmaceutical Design 22, no. 46 (January 24, 2017): 6885–94. http://dx.doi.org/10.2174/1381612822666160831104718.

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Schneider, Petra, and Gisbert Schneider. "Polypharmacological Drug−target Inference for Chemogenomics." Molecular Informatics 37, no. 9-10 (May 24, 2018): 1800050. http://dx.doi.org/10.1002/minf.201800050.

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Seki, Hajime, Song Xue, Mark S. Hixon, Sabine Pellett, Marek Remes̆, Eric A. Johnson, and Kim D. Janda. "Toward the discovery of dual inhibitors for botulinum neurotoxin A: concomitant targeting of endocytosis and light chain protease activity." Chemical Communications 51, no. 28 (2015): 6226–29. http://dx.doi.org/10.1039/c5cc00677e.

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Schneider, P., M. Röthlisberger, D. Reker, and G. Schneider. "Spotting and designing promiscuous ligands for drug discovery." Chemical Communications 52, no. 6 (2016): 1135–38. http://dx.doi.org/10.1039/c5cc07506h.

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Besnard, Jérémy, Gian Filippo Ruda, Vincent Setola, Keren Abecassis, Ramona M. Rodriguiz, Xi-Ping Huang, Suzanne Norval, et al. "Automated design of ligands to polypharmacological profiles." Nature 492, no. 7428 (December 2012): 215–20. http://dx.doi.org/10.1038/nature11691.

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Vitali, Francesca, Francesca Mulas, Pietro Marini, and Riccardo Bellazzi. "Network-based target ranking for polypharmacological therapies." Journal of Biomedical Informatics 46, no. 5 (October 2013): 876–81. http://dx.doi.org/10.1016/j.jbi.2013.06.015.

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Gao, Lanchang, Chao Hao, Ru Ma, Jiali Chen, Guisen Zhang, and Yin Chen. "Synthesis and biological evaluation of a new class of multi-target heterocycle piperazine derivatives as potential antipsychotics." RSC Advances 11, no. 28 (2021): 16931–41. http://dx.doi.org/10.1039/d1ra02426d.

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Li, Hongchun, Fen Pei, D. Lansing Taylor, and Ivet Bahar. "QuartataWeb: Integrated Chemical–Protein-Pathway Mapping for Polypharmacology and Chemogenomics." Bioinformatics 36, no. 12 (March 28, 2020): 3935–37. http://dx.doi.org/10.1093/bioinformatics/btaa210.

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Abstract Summary QuartataWeb is a user-friendly server developed for polypharmacological and chemogenomics analyses. Users can easily obtain information on experimentally verified (known) and computationally predicted (new) interactions between 5494 drugs and 2807 human proteins in DrugBank, and between 315 514 chemicals and 9457 human proteins in the STITCH database. In addition, QuartataWeb links targets to KEGG pathways and GO annotations, completing the bridge from drugs/chemicals to function via protein targets and cellular pathways. It allows users to query a series of chemicals, drug combinations or multiple targets, to enable multi-drug, multi-target, multi-pathway analyses, toward facilitating the design of polypharmacological treatments for complex diseases. Availability and implementation QuartataWeb is freely accessible at http://quartata.csb.pitt.edu. Supplementary information Supplementary data are available at Bioinformatics online.
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Kinnings, Sarah L., Li Xie, Kingston H. Fung, Richard M. Jackson, Lei Xie, and Philip E. Bourne. "The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications." PLoS Computational Biology 6, no. 11 (November 4, 2010): e1000976. http://dx.doi.org/10.1371/journal.pcbi.1000976.

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Dissertations / Theses on the topic "Polypharmacological"

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Dörr, Alexander [Verfasser]. "In Silico Approaches for Polypharmacological Drug Design / Alexander Dörr." München : Verlag Dr. Hut, 2018. http://d-nb.info/1156510287/34.

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Drakakis, Georgios. "Using predicted polypharmacological bioactivity profiles for the analysis of small molecule phenotypic effects." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709193.

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Jall, Sigrid Hedwig [Verfasser], Matthias [Akademischer Betreuer] Tschöp, Matthias [Gutachter] Tschöp, and Johannes [Gutachter] Beckers. "Polypharmacological strategies to reverse obesity and improve multiple aspects of the metabolic syndrome in mice / Sigrid Hedwig Jall ; Gutachter: Matthias Tschöp, Johannes Beckers ; Betreuer: Matthias Tschöp." München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/1211086941/34.

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Melgar, Katelyn M. "A polypharmacologic strategy for overcoming adaptive therapy resistance in AML by targeting immune stress response pathways." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1571061798761171.

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Book chapters on the topic "Polypharmacological"

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Kroeze, Wesley K., and Bryan L. Roth. "Polypharmacological Drugs: “Magic Shotguns” for Psychiatric Diseases." In Polypharmacology in Drug Discovery, 133–48. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118098141.ch7.

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Petrelli, Annalisa. "Polypharmacological Kinase Inhibitors: New Hopes for Cancer Therapy." In Polypharmacology in Drug Discovery, 149–65. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118098141.ch8.

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Brunner, Dani, Vadim Alexandrov, Barbara Caldarone, Taleen Hanania, David Lowe, Jeff Schneider, and Jayaraman Chandrasekhar. "Behavior-Based Screening as an Approach to Polypharmacological Ligands." In Polypharmacology in Drug Discovery, 303–13. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118098141.ch14.

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Conference papers on the topic "Polypharmacological"

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Han, Weiwei, and Lei Xie. "Structural basis of polypharmacological effects of metformin." In 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2012. http://dx.doi.org/10.1109/bibmw.2012.6470337.

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Podlewska, Sabina, and Rafał Kurczab. "Machine-learning-based module for the design of polypharmacological drugs." In 7th International Electronic Conference on Medicinal Chemistry. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/ecmc2021-11361.

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Rao, Suman, Tan Li, Robert Everley, Guangyan Du, Peter Sorger, and Nathanael Gray. "Abstract 1222: Developing kinase inhibitors with polypharmacological profiles for the treatment of resistant cancers." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-1222.

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Papineni, Rao V., Amitava Adhikary, Ritesh Tandon, and Dipanwita Mitra. "Abstract 713: Inhibition of pseudo SARS-CoV-2 binding activity of a anti-cancer polypharmacological agent analogs." In Proceedings: AACR Annual Meeting 2021; April 10-15, 2021 and May 17-21, 2021; Philadelphia, PA. American Association for Cancer Research, 2021. http://dx.doi.org/10.1158/1538-7445.am2021-713.

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