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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Current Neuropharmacology</journal-id><journal-title-group><journal-title xml:lang="en">Current Neuropharmacology</journal-title><trans-title-group xml:lang="ru"><trans-title>Current Neuropharmacology</trans-title></trans-title-group></journal-title-group><issn publication-format="print">1570-159X</issn><issn publication-format="electronic">1875-6190</issn><publisher><publisher-name xml:lang="en">Bentham Science</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">644549</article-id><article-id pub-id-type="doi">10.2174/1570159X22666240515090434</article-id><article-categories><subj-group subj-group-type="toc-heading"><subject>Neurology</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">In Silico Prediction of Quercetin Analogs for Targeting Death-Associated Protein Kinase 1 (DAPK1) Against Alzheimers Disease</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Sun</surname><given-names>Yilu</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Zhao</surname><given-names>Jia</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Lu</surname><given-names>Yizhu</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name><surname>Ngo</surname><given-names>Fung</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name><surname>Shuai</surname><given-names>Bo</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff3"/></contrib><contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Zhang-Jin</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Feng</surname><given-names>Yibin</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name><surname>Rong</surname><given-names>Jianhui</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff id="aff1"><institution>Department of Chinese Medicine, The University of Hong Kong Shenzhen Hospital</institution></aff><aff id="aff2"><institution>School of Chinese Medicine, The University of Hong Kong</institution></aff><aff id="aff3"><institution>Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology</institution></aff><pub-date date-type="pub" iso-8601-date="2024-07-15" publication-format="electronic"><day>15</day><month>07</month><year>2024</year></pub-date><volume>22</volume><issue>14</issue><issue-title xml:lang="ru"/><fpage>2353</fpage><lpage>2367</lpage><history><date date-type="received" iso-8601-date="2025-01-07"><day>07</day><month>01</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Bentham Science Publishers</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Bentham Science Publishers</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/></permissions><self-uri xlink:href="https://journals.eco-vector.com/1570-159X/article/view/644549">https://journals.eco-vector.com/1570-159X/article/view/644549</self-uri><abstract xml:lang="en"><p id="idm46041443536064">:Alzheimers Disease (AD) is a progressive neurodegenerative disorder that greatly affects the health and life quality of the elderly population. Existing drugs mainly alleviate symptoms but fail to halt disease progression, underscoring the urgent need for the development of novel drugs. Based on the neuroprotective effects of flavonoid quercetin in AD, this study was designed to identify potential AD-related targets for quercetin and perform in silico prediction of promising analogs for the treatment of AD. Database mining suggested death-associated protein kinase 1 (DAPK1) as the most promising AD-related target for quercetin among seven protein candidates. To achieve better biological effects for the treatment of AD, we devised a series of quercetin analogs as ligands for DAPK1, and molecular docking analyses, absorption, distribution, metabolism, and excretion (ADME) predictions, as well as molecular dynamics (MD) simulations, were performed. The energy for drug-protein interaction was predicted and ranked. As a result, quercetin-A1a and quercetin-A1a1 out of 19 quercetin analogs exhibited the lowest interaction energy for binding to DAPK1 than quercetin, and they had similar dynamics performance with quercetin. In addition, quercetin-A1a and quercetin-A1a1 were predicted to have better water solubility. Thus, quercetin-A1a and quercetin-A1a1 could be promising agents for the treatment of AD. Our findings paved the way for further experimental studies and the development of novel drugs.</p></abstract><kwd-group xml:lang="en"><kwd>In silico prediction</kwd><kwd>quercetin</kwd><kwd>quercetin analogs</kwd><kwd>death-associated protein kinase 1 (DAPK1)</kwd><kwd>Alzheimer&amp;amp</kwd><kwd>rsquo</kwd><kwd>s disease (AD)</kwd><kwd>neurodegenerative disease.</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Nichols, E.; Szoeke, C.E.I.; Vollset, S.E.; Abbasi, N.; Abd-Allah, F.; Abdela, J.; Aichour, M.T.E.; Akinyemi, R.O.; Alahdab, F.; Asgedom, S.W.; Awasthi, A.; Barker-Collo, S.L.; Baune, B.T.; Béjot, Y.; Belachew, A.B.; Bennett, D.A.; Biadgo, B.; Bijani, A.; Bin Sayeed, M.S.; Brayne, C.; Carpenter, D.O.; Carvalho, F.; Catalá-López, F.; Cerin, E.; Choi, J-Y.J.; Dang, A.K.; Degefa, M.G.; Djalalinia, S.; Dubey, M.; Duken, E.E.; Edvardsson, D.; Endres, M.; Eskandarieh, S.; Faro, A.; Farzadfar, F.; Fereshtehnejad, S-M.; Fernandes, E.; Filip, I.; Fischer, F.; Gebre, A.K.; Geremew, D.; Ghasemi-Kasman, M.; Gnedovskaya, E.V.; Gupta, R.; Hachinski, V.; Hagos, T.B.; Hamidi, S.; Hankey, G.J.; Haro, J.M.; Hay, S.I.; Irvani, S.S.N.; Jha, R.P.; Jonas, J.B.; Kalani, R.; Karch, A.; Kasaeian, A.; Khader, Y.S.; Khalil, I.A.; Khan, E.A.; Khanna, T.; Khoja, T.A.M.; Khubchandani, J.; Kisa, A.; Kissimova-Skarbek, K.; Kivimäki, M.; Koyanagi, A.; Krohn, K.J.; Logroscino, G.; Lorkowski, S.; Majdan, M.; Malekzadeh, R.; März, W.; Massano, J.; Mengistu, G.; Meretoja, A.; Mohammadi, M.; Mohammadi-Khanaposhtani, M.; Mokdad, A.H.; Mondello, S.; Moradi, G.; Nagel, G.; Naghavi, M.; Naik, G.; Nguyen, L.H.; Nguyen, T.H.; Nirayo, Y.L.; Nixon, M.R.; Ofori-Asenso, R.; Ogbo, F.A.; Olagunju, A.T.; Owolabi, M.O.; Panda-Jonas, S.; Passos, V.M.A.; Pereira, D.M.; Pinilla-Monsalve, G.D.; Piradov, M.A.; Pond, C.D.; Poustchi, H.; Qorbani, M.; Radfar, A.; Reiner, R.C., Jr; Robinson, S.R.; Roshandel, G.; Rostami, A.; Russ, T.C.; Sachdev, P.S.; Safari, H.; Safiri, S.; Sahathevan, R.; Salimi, Y.; Satpathy, M.; Sawhney, M.; Saylan, M.; Sepanlou, S.G.; Shafieesabet, A.; Shaikh, M.A.; Sahraian, M.A.; Shigematsu, M.; Shiri, R.; Shiue, I.; Silva, J.P.; Smith, M.; Sobhani, S.; Stein, D.J.; Tabarés-Seisdedos, R.; Tovani-Palone, M.R.; Tran, B.X.; Tran, T.T.; Tsegay, A.T.; Ullah, I.; Venketasubramanian, N.; Vlassov, V.; Wang, Y-P.; Weiss, J.; Westerman, R.; Wijeratne, T.; Wyper, G.M.A.; Yano, Y.; Yimer, E.M.; Yonemoto, N.; Yousefifard, M.; Zaidi, Z.; Zare, Z.; Vos, T.; Feigin, V.L.; Murray, C.J.L. 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