Mostrar el registro sencillo del ítem

In Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysis

dc.contributor.authorMejia-Gutierrez, Melissa
dc.contributor.otherVásquez-Paz, Bryan D
dc.contributor.otherFierro, Leonardo
dc.contributor.otherJulio R. Maza, Julio
dc.date.accessioned2022-12-20T19:13:30Z
dc.date.available2022-12-20T19:13:30Z
dc.date.issued2021-03-30
dc.date.submitted2020-12-09
dc.identifier.citationMejia-Gutierrez, M., Vásquez-Paz, B. D., Fierro, L., & Maza, J. R. (2021). In Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysis. ACS omega, 6(23), 14748–14764. https://doi.org/10.1021/acsomega.0c05984spa
dc.identifier.urihttps://hdl.handle.net/20.500.12834/1158
dc.description.abstractWe have performed theoretical calculations with 70 drugs that have been considered in 231 clinical trials as possible candidates to repurpose drugs for schizophrenia based on their interactions with the dopaminergic system. A hypotheis of shared pharmacophore features was formulated to support our calculations. To do so, we have used the crystal structure of the D2-like dopamine receptor in complex with risperidone, eticlopride, and nemonapride. Linagliptin, citalopram, flunarizine, sildenafil, minocycline, and duloxetine were the drugs that best fit with our model. Molecular docking calculations, molecular dynamics outcomes, blood-brain barrier penetration, and human intestinal absorption were studied and compared with the results. From the six drugs selected in the shared pharmacophore features input, flunarizine showed the best docking score with D2, D3, and D4 dopamine receptors and had high stability during molecular dynamics simulations. Flunarizine is a frequently used medication to treat migraines and vertigo. However, its antipsychotic properties have been previously hypothesized, particularly because of its possible ability to block the D2 dopamine receptors.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceACS Omegaspa
dc.titleIn Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysisspa
dc.title.alternativeIn Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysisspa
dcterms.bibliographicCitationLago, S. G.; Bahn, S. Clinical Trials and Therapeutic Rationale for Drug Repurposing in Schizophrenia. ACS Chem. Neurosci. 2019, 10, 58−78.spa
dcterms.bibliographicCitationSaldívar-González, F.; Prieto-Martínez, F. D.; Medina-Franco, J. L. Descubrimiento y Desarrollo de Farmacos: Un Enfoque ́ Computacional. Educ. Quim. 2017, 28, 51−58spa
dcterms.bibliographicCitationSaldívar-González, F.; Prieto-Martínez, F. D.; Medina-Franco, J. L. Descubrimiento y Desarrollo de Farmacos: Un Enfoque ́ Computacional. Educ. Quim. 2017, 28, 51−58spa
dcterms.bibliographicCitationLau, C.-I.; Wang, H.-C.; Hsu, J.-L.; Liu, M.-E. Does the Dopamine Hypothesis Explain Schizophrenia? Rev. Neurosci. 2013, 24, 389−400.spa
dcterms.bibliographicCitationBeaulieu, J.-M.; Gainetdinov, R. R. The Physiology, Signaling, and Pharmacology of Dopamine Receptors. Pharmacol. Rev. 2011, 63, 182−217spa
dcterms.bibliographicCitationParsons, M. J.; Mata, I.; Beperet, M.; Iribarren-Iriso, F.; Arroyo, B.; Sainz, R.; Arranz, M. J.; Kerwin, R. A Dopamine D2 Receptor Gene-Related Polymorphism Is Associated with Schizophrenia in a Spanish Population Isolate. Psychiatr. Genet. 2007, 17, 159−163.spa
dcterms.bibliographicCitationBertram L. Genetic Research in Schizophrenia: New Tools and Future Perspectives. Schizophr. Bull. 2008, 34, 806–812. 10.1093/schbul/sbn079. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationRondou P.; Haegeman G.; Van Craenenbroeck K. The Dopamine D4 Receptor: Biochemical and Signalling Properties. Cell. Mol. Life Sci. 2010, 67, 1971–1986. 10.1007/s00018-010-0293-y. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGómez-Restrepo C. Guía de práctica clínica para el diagnóstico, tratamiento e inicio de la rehabilitación psicosocial de los adultos con esquizofrenia. Rev. Colomb. Psiquiatr. 2014, 44, 1–2. 10.1016/j.rcp.2015.05.014. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGoto A.; Mouri A.; Nagai T.; Yoshimi A.; Ukigai M.; Tsubai T.; Hida H.; Ozaki N.; Noda Y. Involvement of the Histamine H4 Receptor in Clozapine-Induced Hematopoietic Toxicity: Vulnerability under Granulocytic Differentiation of HL-60 Cells. Toxicol. Appl. Pharmacol. 2016, 306, 8–16. 10.1016/j.taap.2016.06.028. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationSeeman P.; Weinshenker D.; Quirion R.; Srivastava L. K.; Bhardwaj S. K.; Grandy D. K.; Premont R. T.; Sotnikova T. D.; Boksa P.; El-Ghundi M.; et al. Dopamine Supersensitivity Correlates with D2High States, Implying Many Paths to Psychosis. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 3513–3518. 10.1073/pnas.0409766102. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationSeeman P.; Ko F.; Jack E.; Greenstein R.; Dean B. Consistent with Dopamine Supersensitivity, RGS9 Expression Is Diminished in the Amphetamine-Treated Animal Model of Schizophrenia and in Postmortem Schizophrenia Brain. Synapse 2007, 61, 303–309. 10.1002/syn.20368. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGaspar H. A.; Breen G. Drug Enrichment and Discovery from Schizophrenia Genome-Wide Association Results: An Analysis and Visualisation Approach. Sci. Rep. 2017, 7, 12460. 10.1038/s41598-017-12325-3. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationZhao K.; So H.-C. Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data. IEEE J. Biomed. Health Inf. 2019, 23, 1304–1315. 10.1109/JBHI.2018.2856535. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKarunakaran K. B.; Chaparala S.; Ganapathiraju M. K. Potentially Repurposable Drugs for Schizophrenia Identified from Its Interactome. Sci. Rep. 2019, 9, 12682. 10.1038/s41598-019-48307-w. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLee J. H.; Cho S. J.; Kim M.-H. Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening. Molecules 2018, 23, 2452. 10.3390/molecules23102452. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLemos A.; Melo R.; Preto A. J.; Almeida J. G.; Moreira I. S.; Dias Soeiro Cordeiro M. N. In Silico Studies Targeting G-Protein Coupled Receptors for Drug Research Against Parkinson’s Disease. Curr. Neuropharmacol. 2018, 16, 786–848. 10.2174/1570159X16666180308161642. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationIshiki H. M.; Filho J. M. B.; da Silva M. S.; Scotti M. T.; Scotti L. Computer-Aided Drug Design Applied to Parkinson Targets. Curr. Neuropharmacol. 2018, 16, 865–880. 10.2174/1570159X15666171128145423. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationZhao Y.; Lu X.; Yang C.-Y.; Huang Z.; Fu W.; Hou T.; Zhang J. Computational Modeling toward Understanding Agonist Binding on Dopamine 3. J. Chem. Inf. Model. 2010, 50, 1633–1643. 10.1021/ci1002119. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKaserer T.; Beck K. R.; Akram M.; Odermatt A.; Schuster D. Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases. Molecules 2015, 20, 22799–22832. 10.3390/molecules201219880. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationFerraro M.; Decherchi S.; De Simone A.; Recanatini M.; Cavalli A.; Bottegoni G. Multi-Target Dopamine D3 Receptor Modulators: Actionable Knowledge for Drug Design from Molecular Dynamics and Machine Learning. Eur. J. Med. Chem. 2020, 188, 111975. 10.1016/j.ejmech.2019.111975. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBhargava K.; Nath R.; Seth P. K.; Pant K. K.; Dixit R. K. Molecular Docking Studies of D2 Dopamine Receptor with Risperidone Derivatives. Bioinformation 2014, 10, 8–12. 10.6026/97320630010008. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBueschbell B.; Barreto C. A. V.; Preto A. J.; Schiedel A. C.; Moreira I. S. A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods. Molecules 2019, 24, 1196. 10.3390/molecules24071196. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationTrott O.; Olson A. J. AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. J. Comput. Chem. 2010, 31, 455–461. 10.1002/jcc.21334. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKrautscheid Y.; Senning C. J. Å.; Sartori S. B.; Singewald N.; Schuster D.; Stuppner H. Pharmacophore Modeling, Virtual Screening, and in Vitro Testing Reveal Haloperidol, Eprazinone, and Fenbutrazate as Neurokinin Receptors Ligands. J. Chem. Inf. Model. 2014, 54, 1747–1757. 10.1021/ci500106z. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationPatel C. N.; Georrge J. J.; Modi K. M.; Narechania M. B.; Patel D. P.; Gonzalez F. J.; Pandya H. A. Pharmacophore-Based Virtual Screening of Catechol-o-Methyltransferase (COMT) Inhibitors to Combat Alzheimer’s Disease. J. Biomol. Struct. Dyn. 2018, 36, 3938–3957. 10.1080/07391102.2017.1404931. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationFloresta G.; Crocetti L.; Giovannoni M. P.; Biagini P.; Cilibrizzi A. Repurposing Strategies on Pyridazinone-Based Series by Pharmacophore- and Structure-Driven Screening. J. Enzyme Inhib. Med. Chem. 2020, 35, 1137–1144. 10.1080/14756366.2020.1760261. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKagami L. P.; das Neves G. M.; Rodrigues R. P.; da Silva V. B.; Eifler-Lima V. L.; Kawano D. F. Identification of a Novel Putative Inhibitor of the Plasmodium Falciparum Purine Nucleoside Phosphorylase: Exploring the Purine Salvage Pathway to Design New Antimalarial Drugs. Mol. Diversity 2017, 21, 677–695. 10.1007/s11030-017-9745-8. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKumar S.; Chowdhury S.; Kumar S. In Silico Repurposing of Antipsychotic Drugs for Alzheimer’s Disease. BMC Neurosci. 2017, 18, 76. 10.1186/s12868-017-0394-8. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationDilly S.; Fotso Fotso A.; Lejal N.; Zedda G.; Chebbo M.; Rahman F.; Companys S.; Bertrand H. C.; Vidic J.; Noiray M.; et al. From Naproxen Repurposing to Naproxen Analogues and Their Antiviral Activity against Influenza A Virus. J. Med. Chem. 2018, 61, 7202–7217. 10.1021/acs.jmedchem.8b00557. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationTeli M. K.; Rajanikant G. K. Computational Repositioning and Experimental Validation of Approved Drugs for HIF-Prolyl Hydroxylase Inhibition. J. Chem. Inf. Model. 2013, 53, 1818–1824. 10.1021/ci400254a. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMacalino S. J. Y.; Gosu V.; Hong S.; et al. Role of computer-aided drug design in modern drug discovery. Arch. Pharmacal Res. 2015, 38, 1686–1701. 10.1007/s12272-015-0640-5. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLiu X.; Shi D.; Zhou S.; Liu H.; Liu H.; Yao X. Molecular Dynamics Simulations and Novel Drug Discovery. Expert Opin. Drug Discovery 2018, 13, 23–37. 10.1080/17460441.2018.1403419. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationDo P.-C.; Lee E. H.; Le L. Steered Molecular Dynamics Simulation in Rational Drug Design. J. Chem. Inf. Model. 2018, 58, 1473–1482. 10.1021/acs.jcim.8b00261. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationHodos R. A.; Kidd B. A.; Shameer K.; Readhead B. P.; Dudley J. T. In Silico Methods for Drug Repurposing and Pharmacology. Wiley Interdiscip. Rev.: Syst. Biol. Med. 2016, 8, 186–210. 10.1002/wsbm.1337. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationDaina A.; Zoete V. A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. ChemMedChem 2016, 11, 1117–1121. 10.1002/cmdc.201600182. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationTandon R.; Keshavan M. S.; Nasrallah H. A. Schizophrenia, “Just the Facts”: What We Know in 2008 Part 1: Overview. Schizophr. Res. 2008, 100, 4–19. 10.1016/j.schres.2008.01.022. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGaebel W.; Zielasek J. Schizophrenia in 2020: Trends in Diagnosis and Therapy. Psychiatry Clin. Neurosci. 2015, 69, 661–673. 10.1111/pcn.12322. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationSeeman P.; Kapur S. Schizophrenia: More Dopamine, More D2 Receptors. Proc. Natl. Acad. Sci. U. S. A. 2000, 97, 7673–7675. 10.1073/pnas.97.14.7673. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLee T.; Seeman P.. Brain Dopamine Receptors In Schizophrenia; Usdin E., Hanin I. B. T.-B. M. in P. and N., Eds.; Pergamon, 1982; pp. 219–226, 10.1016/B978-0-08-027987-9.50027-5. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationPutnam D. K.; Sun J.; Zhao Z. Exploring Schizophrenia Drug-Gene Interactions through Molecular Network and Pathway Modeling. AMIA . Annual Symposium proceedings. AMIA Annu. Symp. Proc. 2011, 2011, 1127–1133. [PMC free article] [PubMed] [Google Scholar]spa
dcterms.bibliographicCitationKesby J. P.; Eyles D. W.; McGrath J. J.; Scott J. G. Dopamine, Psychosis and Schizophrenia: The Widening Gap between Basic and Clinical Neuroscience. Transl. Psychiatry 2018, 8, 30. 10.1038/s41398-017-0071-9. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLaboratories K. KEEG https://www.genome.jp/kegg/ (accessed Oct 26, 2020).spa
dcterms.bibliographicCitationSibley D. R.; Neve K.Dopamine Receptors; Enna S. J., Bylund D. B. B. T. T. C. P. R., Eds.; Elsevier: New York, 2007; pp. 1–4, 10.1016/B978-008055232-3.60151-5. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationNeve K. A.Dopamine Receptors; Lennarz W. J., Lane M. D. B. T.-E. of B. C. (Second E., Eds.; Academic Press: Waltham, 2013; pp. 169–173, 10.1016/B978-0-12-378630-2.00326-1. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWang S.; Che T.; Levit A.; Shoichet B. K.; Wacker D.; Roth B. L. Structure of the D2 Dopamine Receptor Bound to the Atypical Antipsychotic Drug Risperidone. Nature 2018, 555, 269–273. 10.1038/nature25758. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationCorena-McLeod M. Comparative Pharmacology of Risperidone and Paliperidone. Drugs R&D 2015, 15, 163–174. 10.1007/s40268-015-0092-x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMartelle J. L.; Nader M. A. A Review of the Discovery, Pharmacological Characterization, and Behavioral Effects of the Dopamine D2-like Receptor Antagonist Eticlopride. CNS Neurosci. Ther. 2008, 14, 248–262. 10.1111/j.1755-5949.2008.00047.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMiyamoto S.Nemonapride BT - Encyclopedia of Psychopharmacology; Stolerman I. P., Ed.; Springer Berlin Heidelberg: Berlin, Heidelberg, 2010; p 823, 10.1007/978-3-540-68706-1_1840. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationPlatania C. B. M.; Salomone S.; Leggio G. M.; Drago F.; Bucolo C. Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation. PLoS One 2012, 7, e44316–e44316. 10.1371/journal.pone.0044316. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationChien E. Y. T.; Liu W.; Zhao Q.; Katritch V.; Han G. W.; Hanson M. A.; Shi L.; Newman A. H.; Javitch J. A.; Cherezov V.; Stevens R. C. Structure of the human dopamine D3 receptor in complex with a D2/D3 selective antagonist. Science 2010, 330, 1091–1095. 10.1126/science.1197410. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationFerreira de Freitas R.; Schapira M. A Systematic Analysis of Atomic Protein–Ligand Interactions in the PDB. MedChemComm 2017, 8, 1970–1981. 10.1039/C7MD00381A. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWang S.; Wacker D.; Levit A.; Che T.; Betz R. M.; McCorvy J. D.; Venkatakrishnan A. J.; Huang X.-P.; Dror R. O.; Shoichet B. K.; Roth B. L. D4 Dopamine Receptor High-Resolution Structures Enable the Discovery of Selective Agonists. Science 2017, 358, 381–386. 10.1126/science.aan5468. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationVanommeslaeghe K.; Hatcher E.; Acharya C.; Kundu S.; Zhong S.; Shim J.; Darian E.; Guvench O.; Lopes P.; Vorobyov I.; Mackerell A. D. Jr. CHARMM General Force Field: A Force Field for Drug-like Molecules Compatible with the CHARMM All-Atom Additive Biological Force Fields. J. Comput. Chem. 2010, 31, 671–690. 10.1002/jcc.21367. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationJean B.; Surratt C. K.; Madura J. D. Molecular Dynamics of Conformation-Specific Dopamine Transporter-Inhibitor Complexes. J. Mol. Graphics Modell. 2017, 76, 143–151. 10.1016/j.jmgm.2017.07.003. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationHuang J.; Rauscher S.; Nawrocki G.; Ran T.; Feig M.; de Groot B. L.; Grubmüller H.; MacKerell A. D. Jr. CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nat. Methods 2017, 14, 71–73. 10.1038/nmeth.4067. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationNielsen A. K.; Möller I. R.; Wang Y.; Rasmussen S. G. F.; Lindorff-Larsen K.; Rand K. D.; Loland C. J. Substrate-Induced Conformational Dynamics of the Dopamine Transporter. Nat. Commun. 2019, 10, 2714. 10.1038/s41467-019-10449-w. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKlauda J. B.; Venable R. M.; Freites J. A.; O’Connor J. W.; Tobias D. J.; Mondragon-Ramirez C.; Vorobyov I.; MacKerell A. D. Jr.; Pastor R. W. Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 2010, 114, 7830–7843. 10.1021/jp101759q. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationVanommeslaeghe K.; MacKerell A. D. Jr. Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 2012, 52, 3144–3154. 10.1021/ci300363c. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBest R. B.; Zhu X.; Shim J.; Lopes P. E. M.; Mittal J.; Feig M.; Mackerell A. D. Jr. Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone φ, ψ and Side-Chain χ(1) and χ(2) Dihedral Angles. J. Chem. Theory Comput. 2012, 8, 3257–3273. 10.1021/ct300400x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLane J. R.; Abramyan A. M.; Adhikari P.; Keen A. C.; Lee K.-H.; Sanchez J.; Verma R. K.; Lim H. D.; Yano H.; Javitch J. A.; Shi L. Distinct Inactive Conformations of the Dopamine D2 and D3 Receptors Correspond to Different Extents of Inverse Agonism. eLife 2020, 9, e52189 10.7554/eLife.52189. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMacKerell A. D. Jr.; Feig M.; Brooks C. L. Improved Treatment of the Protein Backbone in Empirical Force Fields. J. Am. Chem. Soc. 2004, 126, 698–699. 10.1021/ja036959e. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationJo J. C.; Kim B. C. Determination of Proper Time Step for Molecular Dynamics Simulation. Bull. Korean Chem. Soc. 2000, 21, 419. [Google Scholar]spa
dcterms.bibliographicCitationHollingsworth S. A.; Dror R. O. Molecular Dynamics Simulation for All. Neuron 2018, 99, 1129–1143. 10.1016/j.neuron.2018.08.011. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLobanov M. Y.; Bogatyreva N. S.; Galzitskaya O. V. Radius of Gyration as an Indicator of Protein Structure Compactness. Mol. Biol. 2008, 42, 623–628. 10.1134/S0026893308040195. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationFalsafi-Zadeh S.; Karimi Z.; Galehdari H. VMD DisRg: New User-Friendly Implement for Calculation Distance and Radius of Gyration in VMD Program. Bioinformation 2012, 8, 341–343. 10.6026/97320630008341. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationShao J.; Tanner S. W.; Thompson N.; Cheatham T. E. Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms. J. Chem. Theory Comput. 2007, 3, 2312–2334. 10.1021/ct700119m. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWu X.; Wang S. Self-Guided Molecular Dynamics Simulation for Efficient Conformational Search. J. Phys. Chem. B 1998, 102, 7238–7250. 10.1021/jp9817372. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWu X.; Brooks B. R. Beta-Hairpin Folding Mechanism of a Nine-Residue Peptide Revealed from Molecular Dynamics Simulations in Explicit Water. Biophys. J. 2004, 86, 1946–1958. 10.1016/S0006-3495(04)74258-7. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWu X.; Wang S. Helix Folding of an Alanine-Based Peptide in Explicit Water. J. Phys. Chem. B 2001, 105, 2227–2235. 10.1021/jp004048a. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBisol L. W.; Brunstein M. G.; Ottoni G. L.; Ramos F. L. P.; Borba D. L.; Daltio C. S.; de Oliveira R. V.; Paz G. E. G.; de Souza S. E.; Bressan R. A.; Lara D. R. Is Flunarizine a Long-Acting Oral Atypical Antipsychotic? A Randomized Clinical Trial versus Haloperidol for the Treatment of Schizophrenia. J. Clin. Psychiatry 2008, 69, 1572–1579. 10.4088/jcp.v69n1007. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAmbrosio C.; Stefanini E. Interaction of Flunarizine with Dopamine D2 and D1 Receptors. Eur. J. Pharmacol. 1991, 197, 221–223. 10.1016/0014-2999(91)90526-v. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWöber C.; Brücke T.; Wöber-Bingöl C.; Asenbaum S.; Wessely P.; Podreka I. Dopamine D2 Receptor Blockade and Antimigraine Action of Flunarizine. Cephalalgia 1994, 14, 235–240. 10.1046/j.1468-2982.1994.014003235.x. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationYan Y.; Pan J.; Chen Y.; Xing W.; Li Q.; Wang D.; Zhou X.; Xie J.; Miao C.; Yuan Y.; Zeng W.; Chen D. Increased Dopamine and Its Receptor Dopamine Receptor D1 Promote Tumor Growth in Human Hepatocellular Carcinoma. Cancer Commun. 2020, 694. 10.1002/cac2.12103. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKafka S. H.; Corbett R. Selective Adenosine A2A Receptor/Dopamine D2 Receptor Interactions in Animal Models of Schizophrenia. Eur. J. Pharmacol. 1996, 295, 147–154. 10.1016/0014-2999(95)00668-0. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBelforte J. E.; Magariños-Azcone C.; Armando I.; Buño W.; Pazo J. H. Pharmacological Involvement of the Calcium Channel Blocker Flunarizine in Dopamine Transmission at the Striatum. Parkinsonism Relat. Disord. 2001, 8, 33–40. 10.1016/s1353-8020(01)00006-2. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKarsan N.; Palethorpe D.; Rattanawong W.; Marin J. C.; Bhola R.; Goadsby P. J. Flunarizine in Migraine-Related Headache Prevention: Results from 200 Patients Treated in the UK. Eur. J. Neurol. 2018, 25, 811–817. 10.1111/ene.13621. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAmery W. K.; Caers L. I.; Aerts T. J. L. Flunarizine, a Calcium Entry Blocker in Migraine Prophylaxis. J. Headache Pain 1985, 25, 249–254. 10.1111/j.1526-4610.1985.hed2505249.x. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationPiccini P.; Nuti A.; Paoletti A. M.; Napolitano A.; Melis G. B.; Bonuccelli U. Possible Involvement of Dopaminergic Mechanisms in the Antimigraine Action of Flunarizine. Cephalalgia 1990, 10, 3–8. 10.1046/j.1468-2982.1990.1001003.x. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationFrisch M. J.et al. Gaussian 09, Revision B.01, Gaussian, Inc.2009. [Google Scholar]spa
dcterms.bibliographicCitationO’Boyle N. M.; Banck M.; James C. A.; Morley C.; Vandermeersch T.; Hutchison G. R. Open Babel: An Open Chemical Toolbox. J. Cheminf. 2011, 3, 33. 10.1186/1758-2946-3-33. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationJaiteh M.; Rodríguez-Espigares I.; Selent J.; Carlsson J. Performance of Virtual Screening against GPCR Homology Models: Impact of Template Selection and Treatment of Binding Site Plasticity. PLoS Comput. Biol. 2020, 16, e1007680–e1007680. 10.1371/journal.pcbi.1007680. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMorris G. M.; Lim-Wilby M. Molecular Docking. Methods Mol. Biol. 2008, 443, 365–382. 10.1007/978-1-59745-177-2_19. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationPettersen E. F.; Goddard T. D.; Huang C. C.; Couch G. S.; Greenblatt D. M.; Meng E. C.; Ferrin T. E. UCSF Chimera--a Visualization System for Exploratory Research and Analysis. J. Comput. Chem. 2004, 25, 1605–1612. 10.1002/jcc.20084. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGuner O.; Clement O.; Kurogi Y. Pharmacophore Modeling and Three Dimensional Database Searching for Drug Design Using Catalyst: Recent Advances. Curr. Med. Chem. 2004, 11, 2991–3005. 10.2174/0929867043364036. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationCheng F.; Li W.; Zhou Y.; Shen J.; Wu Z.; Liu G.; Lee P. W.; Tang Y. AdmetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. J. Chem. Inf. Model. 2012, 52, 3099–3105. 10.1021/ci300367a. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAnbu V.; Karthick T.; Vijayalakshmi K. A. Combined Experimental and Computational Approach for the Vibrational Characteristics and Theoretical Evaluation of Binding Activities and ADME Descriptors of 2,6-Di-Tert-Butyl-p-Cresol. Polycyclic Aromat. Compd. 2020, 1–17. 10.1080/10406638.2020.1768567. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationNewby D.; Freitas A. A.; Ghafourian T. Decision Trees to Characterise the Roles of Permeability and Solubility on the Prediction of Oral Absorption. Eur. J. Med. Chem. 2015, 90, 751–765. 10.1016/j.ejmech.2014.12.006. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationUrsu O.; Rayan A.; Goldblum A.; Oprea T. I. Understanding Drug-Likeness. WIREs Comput. Mol. Sci. 2011, 1, 760–781. 10.1002/wcms.52. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationRankovic Z. CNS Drug Design: Balancing Physicochemical Properties for Optimal Brain Exposure. J. Med. Chem. 2015, 58, 2584–2608. 10.1021/jm501535r. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGhose A. K.; Herbertz T.; Hudkins R. L.; Dorsey B. D.; Mallamo J. P. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery. ACS Chem. Neurosci. 2012, 3, 50–68. 10.1021/cn200100h. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationZafar F.; Gupta A.; Thangavel K.; Khatana K.; Sani A. A.; Ghosal A.; Tandon P.; Nishat N. Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives. ACS Omega 2020, 5, 6021–6030. 10.1021/acsomega.9b04398. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationSingh N.; Kumar N.; Rathee G.; Sood D.; Singh A.; Tomar V.; Dass S. K.; Chandra R. Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches. ACS Omega 2020, 5, 2267–2279. 10.1021/acsomega.9b03479. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAl-Blewi F.; Rezki N.; Naqvi A.; Qutb Uddin H.; Al-Sodies S.; Messali M.; Aouad M. R.; Bardaweel S. A Profile of the In Vitro Anti-Tumor Activity and In Silico ADME Predictions of Novel Benzothiazole Amide-Functionalized Imidazolium Ionic Liquids. Int. J. Mol. Sci. 2019, 20, 2865. 10.3390/ijms20122865. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAhmad S. S.; Sinha M.; Ahmad K.; Khalid M.; Choi I. Study of Caspase 8 Inhibition for the Management of Alzheimer’s Disease: A Molecular Docking and Dynamics Simulation. Molecules 2020, 25, 2071. 10.3390/molecules25092071. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationLoureiro D. R. P.; Soares J. X.; Costa J. C.; Magalhães Á. F.; Azevedo C. M. G.; Pinto M. M. M.; Afonso C. M. M. Structures, Activities and Drug-Likeness of Anti-Infective Xanthone Derivatives Isolated from the Marine Environment: A Review. Molecules 2019, 24, 243. 10.3390/molecules24020243. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKehinde I.; Ramharack P.; Nlooto M.; Gordon M. The Pharmacokinetic Properties of HIV-1 Protease Inhibitors: A Computational Perspective on Herbal Phytochemicals. Heliyon 2019, 5, e02565–e02565. 10.1016/j.heliyon.2019.e02565. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationGarg P.; Verma J.; Roy N. In Silico Modeling for Blood—Brain Barrier Permeability Predictions. Drug Absorpt. Stud. 2008, 510–556. 10.1007/978-0-387-74901-3_22. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationBerendsen H. J. C.; van der Spoel D.; van Drunen R. GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. Comput. Phys. Commun. 1995, 91, 43–56. 10.1016/0010-4655(95)00042-E. [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationHess B.; Kutzner C.; van der Spoel D.; Lindahl E. GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435–447. 10.1021/ct700301q. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationvan der Spoel D.; Lindahl E.; Hess B.; Groenhof G.; Mark A. E.; Berendsen H. J. C. GROMACS: Fast, Flexible, and Free. J. Comput. Chem. 2005, 26, 1701–1718. 10.1002/jcc.20291. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationMichino M.; Boateng C. A.; Donthamsetti P.; Yano H.; Bakare O. M.; Bonifazi A.; Ellenberger M. P.; Keck T. M.; Kumar V.; Zhu C.; Verma R.; Deschamps J. R.; Javitch J. A.; Newman A. H.; Shi L. Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor. J. Med. Chem. 2017, 60, 580–593. 10.1021/acs.jmedchem.6b01148. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationWassenaar T. A.; Mark A. E. The Effect of Box Shape on the Dynamic Properties of Proteins Simulated under Periodic Boundary Conditions. J. Comput. Chem. 2006, 27, 316–325. 10.1002/jcc.20341. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationAli J.; Camilleri P.; Brown M. B.; Hutt A. J.; Kirton S. B. In Silico Prediction of Aqueous Solubility Using Simple QSPR Models: The Importance of Phenol and Phenol-like Moieties. J. Chem. Inf. Model. 2012, 52, 2950–2957. 10.1021/ci300447c. [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationOkuda S.; Yamada T.; Hamajima M.; Itoh M.; Katayama T.; Bork P.; Goto S.; Kanehisa M. KEGG Atlas Mapping for Global Analysis of Metabolic Pathways. Nucleic Acids Res. 2008, 36, W423–W426. 10.1093/nar/gkn282. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKanehisa M.; Goto S.; Sato Y.; Furumichi M.; Tanabe M. KEGG for Integration and Interpretation of Large-Scale Molecular Data Sets. Nucleic Acids Res. 2012, 40, D109–D114. 10.1093/nar/gkr988. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
dcterms.bibliographicCitationKanehisa M.; Goto S.; Furumichi M.; Tanabe M.; Hirakawa M. KEGG for Representation and Analysis of Molecular Networks Involving Diseases and Drugs. Nucleic Acids Res. 2010, 38, D355–D360. 10.1093/nar/gkp896. [PMC free article] [PubMed] [CrossRef] [Google Scholar]spa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.audiencePúblico generalspa
dc.identifier.doi10.1021/acsomega.0c05984
dc.identifier.instnameUniversidad del Atlánticospa
dc.identifier.reponameRepositorio Universidad del Atlánticospa
dc.rights.ccAttribution-NonCommercial 4.0 International*
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionspa
dc.type.spaArtículospa
dc.publisher.placeBarranquillaspa
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessspa
dc.publisher.disciplineQuímicaspa
dc.publisher.sedeSede Nortespa


Ficheros en el ítem

Thumbnail
Nombre:
In_Silico_Repositioning_of_Dop ...
Tamaño:
7.859Mb
Formato:
PDF
Ver/
Thumbnail
Nombre:
license_rdf
Tamaño:
914bytes
Formato:
application/rdf+xml
Ver/

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

http://creativecommons.org/licenses/by-nc/4.0/
Excepto si se señala otra cosa, la licencia del ítem se describe como http://creativecommons.org/licenses/by-nc/4.0/

UNIVERSIDAD DEL ATLÁNTICO

Institución Pública de Educación Superior | Sujeta a la inspección y vigilancia del Ministerio de Educación Nacional | Nit. 890102257-3
Sede Norte: Carrera 30 Número 8- 49 Puerto Colombia - Atlántico | Sede Centro: Carrera 43 Número 50 - 53 Barranquilla- Atlántico.
Bellas Artes- Museo de Antropología: Calle 68 Número 53- 45 Barranquilla- Atlántico | Sede Regional Sur: Calle 7 No. 23-5 Barrio Abajo Suan- Atlántico
Línea de atención: PBX: (57) (5) 3852266 | Atlántico- Colombia | © Universidad del Atlántico
#UniversidadDeTodos

Resolución de lineamientos del repositorio - Estatuto de propiedad intelectual - Formato para trabajos de grado - Politicas Repositorio Institucional

Tecnología DSpace implementada por