Conducting 2D and 3D QSAR Analyses and Molecular Docking Studies of
Analogues of 2-(1-(1,3,4-thiadiazol-2-yl)piperidin-4-yl)ethan-1-ol with the
Aim of Identifying Promising Drug Candidates for Targeting Glioblastoma

Meichen      Pan; Lingxue      Cheng; Yiguo      Wang; Chunyi      Lyu; Chao      Hou; Qiming      Zhang

doi:10.2174/1570180820666230901162718

Abstract

Background: 2-(1-(1,3,4-thiadiazol-2-yl)piperidin-4-yl) ethan-1-ol analogues represent novel glutaminase 1 inhibitors. Their exemplary antineoplastic efficacy underscores their prospective utility in glioblastoma chemotherapy.

Objective: This study aimed to elucidate 2D and 3D-QSAR models that authenticate the antineoplastic efficacy of ethan-1-ol analogues and delineate optimal structural configurations conducive to new pharmaceutical design.

Methods: The Heuristic Method (HM) was employed for the development of a 2D-linear QSAR paradigm, whilst the Gene Expression Programming (GEP) algorithm was employed for a 2D-nonlinear QSAR paradigm. Concurrently, the CoMSIA methodology was deployed to scrutinize the nexus between pharmaceutical structure and potency. An ensemble of 200 nascent anti-glioma ethan-1-ol compounds was conceptualized, and their potency levels were prognosticated via chemical descriptors and molecular field delineations. Pharmaceuticals epitomizing peak potency were earmarked for molecular docking validation.

Results: The empirical modeling exhibited pronounced superiority with the 3D paradigm, succeeded by the GEP nonlinear paradigm and culminated with the HM linear model. The 3D paradigm was characterized by a robust Q2 (0.533), R2 (0.921), and F-values (132.338) complemented by a minimal SEE (0.110). The molecular descriptor MNO coupled with the hydrogen bond donor field facilitated novel pharmaceutical conceptualizations, leading to the identification of the quintessential active molecule, 24J.138, lauded for its superlative antineoplastic attributes and docking proficiency.

Conclusion: The orchestration of bidimensional and tridimensional paradigms, synergized by innovative amalgamation of contour maps and molecular descriptors, provides novel insights and methodologies for the synthesis of glioblastoma chemotherapeutic agents.

Keywords: Glioblastoma, drug design, ethan-1-ol analogues, QSAR, glutaminase 1, molecule docking.

« Previous

Graphical Abstract

[1]
Wang, Y.; Jiang, T. Understanding high grade glioma: Molecular mechanism, therapy and comprehensive management. Cancer Lett.,  2013, 331(2), 139-146.
 [http://dx.doi.org/10.1016/j.canlet.2012.12.024] [PMID: 23340179]

[2]
Schiff, D.; Van den Bent, M.; Vogelbaum, M.A.; Wick, W.; Miller, C.R.; Taphoorn, M.; Pope, W.; Brown, P.D.; Platten, M.; Jalali, R.; Armstrong, T.; Wen, P.Y. Recent developments and future directions in adult lower-grade gliomas: Society for Neuro-Oncology (SNO) and European Association of Neuro-Oncology (EANO) consensus. Neuro-oncol.,  2019, 21(7), 837-853.
 [http://dx.doi.org/10.1093/neuonc/noz033] [PMID: 30753579]

[3]
Márquez, J.; Alonso, F.J.; Matés, J.M.; Segura, J.A.; Martín-Rufián, M.; Campos-Sandoval, J.A. Glutamine addiction in gliomas. Neurochem. Res.,  2017, 42(6), 1735-1746.
 [http://dx.doi.org/10.1007/s11064-017-2212-1] [PMID: 28281102]

[4]
Doan, P.; Musa, A.; Murugesan, A.; Sipilä, V.; Candeias, N.R.; Emmert-Streib, F.; Ruusuvuori, P.; Granberg, K.; Yli-Harja, O.; Kandhavelu, M. Glioblastoma multiforme stem cell cycle arrest by alkylaminophenol through the modulation of EGFR and CSC signaling pathways. Cells,  2020, 9(3), 681.
 [http://dx.doi.org/10.3390/cells9030681] [PMID: 32164385]

[5]
Weller, R. World p-ark. wild la+ interdiscip. J Landsc Archit.,  2015, 1, 10-19.

[6]
Knudsen, B.; Fischer, M.H.; Aschersleben, G. Development of spatial preferences for counting and picture naming. Psychol. Res.,  2015, 79(6), 939-949.
 [http://dx.doi.org/10.1007/s00426-014-0623-z] [PMID: 25326847]

[7]
Davis, M. Glioblastoma: Overview of disease and treatment. Clin. J. Oncol. Nurs.,  2016, 20(5)(Suppl.), S2-S8.
 [http://dx.doi.org/10.1188/16.CJON.S1.2-8] [PMID: 27668386]

[8]
Young, R.M.; Jamshidi, A.; Davis, G.; Sherman, J.H. Current trends in the surgical management and treatment of adult glioblastoma. Ann. Transl. Med.,  2015, 3(9), 121.
 [PMID: 26207249]

[9]
Tan, A.C.; Ashley, D.M.; López, G.Y.; Malinzak, M.; Friedman, H.S.; Khasraw, M. Management of glioblastoma: State of the art and future directions. CA Cancer J. Clin.,  2020, 70(4), 299-312.
 [http://dx.doi.org/10.3322/caac.21613] [PMID: 32478924]

[10]
Saito, R. Chemotherapy for glioma. No Shinkei Geka,  2021, 49(3), 588-596.
 [PMID: 34092564]

[11]
Skinner, M.; Ward, S.M.; Nilsson, C.L.; Emrick, T. Augmenting glioblastoma chemotherapy with polymers. ACS Chem. Neurosci.,  2018, 9(1), 8-10.
 [http://dx.doi.org/10.1021/acschemneuro.7b00168] [PMID: 28594164]

[12]
Lombardi, G.; Pambuku, A.; Bellu, L.; Farina, M.; Della Puppa, A.; Denaro, L.; Zagonel, V. Effectiveness of antiangiogenic drugs in glioblastoma patients: A systematic review and meta-analysis of randomized clinical trials. Crit. Rev. Oncol. Hematol.,  2017, 111, 94-102.
 [http://dx.doi.org/10.1016/j.critrevonc.2017.01.018] [PMID: 28259301]

[13]
Diaz, R.J.; Ali, S.; Qadir, M.G.; De La Fuente, M.I.; Ivan, M.E.; Komotar, R.J. The role of bevacizumab in the treatment of glioblastoma. J. Neurooncol.,  2017, 133(3), 455-467.
 [http://dx.doi.org/10.1007/s11060-017-2477-x] [PMID: 28527008]

[14]
Tarrado-Castellarnau, M.; de Atauri, P.; Cascante, M. Oncogenic regulation of tumor metabolic reprogramming. Oncotarget,  2016, 7(38), 62726-62753.
 [http://dx.doi.org/10.18632/oncotarget.10911] [PMID: 28040803]

[15]
Warburg, O.; Wind, F.; Negelein, E. The metabolism of tumors in the body. J. Gen. Physiol.,  1927, 8(6), 519-530.
 [http://dx.doi.org/10.1085/jgp.8.6.519] [PMID: 19872213]

[16]
Hensley, C.T.; Wasti, A.T.; DeBerardinis, R.J. Glutamine and cancer: Cell biology, physiology, and clinical opportunities. J. Clin. Invest.,  2013, 123(9), 3678-3684.
 [http://dx.doi.org/10.1172/JCI69600] [PMID: 23999442]

[17]
Le, A.; Lane, A.N.; Hamaker, M.; Bose, S.; Gouw, A.; Barbi, J.; Tsukamoto, T.; Rojas, C.J.; Slusher, B.S.; Zhang, H.; Zimmerman, L.J.; Liebler, D.C.; Slebos, R.J.C.; Lorkiewicz, P.K.; Higashi, R.M.; Fan, T.W.M.; Dang, C.V. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab.,  2012, 15(1), 110-121.
 [http://dx.doi.org/10.1016/j.cmet.2011.12.009] [PMID: 22225880]

[18]
Son, J.; Lyssiotis, C.A.; Ying, H.; Wang, X.; Hua, S.; Ligorio, M.; Perera, R.M.; Ferrone, C.R.; Mullarky, E.; Shyh-Chang, N.; Kang, Y.; Fleming, J.B.; Bardeesy, N.; Asara, J.M.; Haigis, M.C.; DePinho, R.A.; Cantley, L.C.; Kimmelman, A.C. Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature,  2013, 496(7443), 101-105.
 [http://dx.doi.org/10.1038/nature12040] [PMID: 23535601]

[19]
Gaglio, D.; Metallo, C.M.; Gameiro, P.A.; Hiller, K.; Danna, L.S.; Balestrieri, C.; Alberghina, L.; Stephanopoulos, G.; Chiaradonna, F. Oncogenic K Ras decouples glucose and glutamine metabolism to support cancer cell growth. Mol. Syst. Biol.,  2011, 7(1), 523.
 [http://dx.doi.org/10.1038/msb.2011.56] [PMID: 21847114]

[20]
Xu, X.; Chang, X.; Huang, J.; Zhang, D.; Wang, M.; Jing, T.; Zhuang, Y.; Kou, J.; Qiu, Z.; Wang, J.; Li, Z.; Bian, J. Discovery of novel glutaminase 1 allosteric inhibitor with 4-piperidinamine linker and aromatic heterocycles. Eur. J. Med. Chem.,  2022, 236, 114337.
 [http://dx.doi.org/10.1016/j.ejmech.2022.114337] [PMID: 35428013]

[21]
Carbone, D.; Vestuto, V.; Ferraro, M.R.; Ciaglia, T.; Pecoraro, C.; Sommella, E.; Cascioferro, S.; Salviati, E.; Novi, S.; Tecce, M.F.; Amodio, G.; Iraci, N.; Cirrincione, G.; Campiglia, P.; Diana, P.; Bertamino, A.; Parrino, B.; Ostacolo, C. Metabolomics-assisted discovery of a new anticancer GLS-1 inhibitor chemotype from a nortopsentin-inspired library: From phenotype screening to target identification. Eur. J. Med. Chem.,  2022, 234, 114233.
 [http://dx.doi.org/10.1016/j.ejmech.2022.114233] [PMID: 35286926]

[22]
Reinfeld, B.I.; Madden, M.Z.; Wolf, M.M.; Chytil, A.; Bader, J.E.; Patterson, A.R.; Sugiura, A.; Cohen, A.S.; Ali, A.; Do, B.T.; Muir, A.; Lewis, C.A.; Hongo, R.A.; Young, K.L.; Brown, R.E.; Todd, V.M.; Huffstater, T.; Abraham, A.; O’Neil, R.T.; Wilson, M.H.; Xin, F.; Tantawy, M.N.; Merryman, W.D.; Johnson, R.W.; Williams, C.S.; Mason, E.F.; Mason, F.M.; Beckermann, K.E.; Vander Heiden, M.G.; Manning, H.C.; Rathmell, J.C.; Rathmell, W.K. Cell-programmed nutrient partitioning in the tumour microenvironment. Nature,  2021, 593(7858), 282-288.
 [http://dx.doi.org/10.1038/s41586-021-03442-1] [PMID: 33828302]

[23]
Mohammed, M.S.; Kovalev, I.S.; Slovesnova, N.V.; Sadieva, L.K.; Platonov, V.A.; Kim, G.A.; Aluru, R.; Novikov, A.S.; Taniya, O.S.; Charushin, V.N. (1-(4-(5-Phenyl-1,3,4-oxadiazol-2-yl)phenyl)-1H-1,2,3-triazol-4-yl)-methylenyls α,ω-Bisfunctionalized 3- and 4-PEG: Synthesis and photophysical studies. Molecules,  2023, 28(13), 5256.
 [http://dx.doi.org/10.3390/molecules28135256] [PMID: 37446917]

[24]
Il’in, M.V.; Sysoeva, A.A.; Bolotin, D.S.; Novikov, A.S.; Suslonov, V.V.; Rogacheva, E.V.; Kraeva, L.A.; Kukushkin, V.Y. Aminonitrones as highly reactive bifunctional synthons. An expedient one-pot route to 5-amino-1,2,4-triazoles and 5-amino-1,2,4-oxadiazoles: Potential antimicrobials targeting multi-drug resistant bacteria. New J. Chem.,  2019, 43(44), 17358-17366.
 [http://dx.doi.org/10.1039/C9NJ04529E]

[25]
Melekhova, A.A.; Smirnov, A.S.; Novikov, A.S.; Panikorovskii, T.L.; Bokach, N.A.; Kukushkin, V.Y. Copper(I)-catalyzed 1,3-dipolar cycloaddition of ketonitrones to dialkylcyanamides: A step toward sustainable generation of 2,3-dihydro-1,2,4-oxadiazoles. ACS Omega,  2017, 2(4), 1380-1391.
 [http://dx.doi.org/10.1021/acsomega.7b00130] [PMID: 31457510]

[26]
Grudova, M.V.; Kubasov, A.S.; Khrustalev, V.N.; Novikov, A.S.; Kritchenkov, A.S.; Nenajdenko, V.G.; Borisov, A.V.; Tskhovrebov, A.G. Exploring supramolecular assembly space of cationic 1,2,4-selenodiazoles: Effect of the substituent at the carbon atom and anions. Molecules,  2022, 27(3), 1029.
 [http://dx.doi.org/10.3390/molecules27031029] [PMID: 35164294]

[27]
Lavrenova, L.G.; Ivanova, A.I.; Glinskaya, L.A.; Artem’ev, A.V.; Lavrov, A.N.; Novikov, A.S.; Abramov, P.A. Halogen bonding
channels for magnetic exchange in Cu(II) complexes with 2,5
Di(methylthio) 1,3,4 thiadiazole. Chem. Asian J.,  2023, 18(4), e202201200.
 [http://dx.doi.org/10.1002/asia.202201200] [PMID: 36629842]

[28]
Mikherdov, A.; Novikov, A.; Kinzhalov, M.; Zolotarev, A.; Boyarskiy, V. Intra-/intermolecular bifurcated chalcogen bonding in crystal structure of thiazole/thiadiazole derived binuclear (Diaminocarbene)PdII complexes. Crystals,  2018, 8(3), 112.
 [http://dx.doi.org/10.3390/cryst8030112]

[29]
Khrustalev, V.N.; Grishina, M.M.; Matsulevich, Z.V.; Lukiyanova, J.M.; Borisova, G.N.; Osmanov, V.K.; Novikov, A.S.; Kirichuk, A.A.; Borisov, A.V.; Solari, E.; Tskhovrebov, A.G. Novel cationic 1,2,4-selenadiazoles: Synthesis via addition of 2-pyridylselenyl halides to unactivated nitriles, structures and four-center Se⋯N contacts. Dalton Trans.,  2021, 50(31), 10689-10691.
 [http://dx.doi.org/10.1039/D1DT01322J] [PMID: 34165455]

[30]
Kulish, K.I.; Novikov, A.S.; Tolstoy, P.M.; Bolotin, D.S.; Bokach, N.A.; Zolotarev, A.A.; Kukushkin, V.Y. Solid state and dynamic solution structures of O-carbamidine amidoximes gives further insight into the mechanism of zinc(II)-mediated generation of 1,2,4-oxadiazoles. J. Mol. Struct.,  2016, 1111, 142-150.
 [http://dx.doi.org/10.1016/j.molstruc.2016.01.038]

[31]
Bolotin, D.S.; Il’in, M.V.; Novikov, A.S.; Bokach, N.A.; Suslonov, V.V.; Kukushkin, V.Y. Trinuclear (aminonitrone)Zn II complexes as key intermediates in zinc(II)-mediated generation of 1,2,4-oxadiazoles from amidoximes and nitriles. New J. Chem.,  2017, 41(5), 1940-1952.
 [http://dx.doi.org/10.1039/C6NJ03508F]

[32]
Baykov, S.V.; Mikherdov, A.S.; Novikov, A.S.; Geyl, K.K.; Tarasenko, M.V.; Gureev, M.A.; Boyarskiy, V.P. π–π noncovalent interaction involving 1,2,4- and 1,3,4-oxadiazole systems: The combined experimental, theoretical, and database study. Molecules,  2021, 26(18), 5672.
 [http://dx.doi.org/10.3390/molecules26185672] [PMID: 34577142]

[33]
Matés, J.M.; Segura, J.A.; Martín-Rufián, M.; Campos-Sandoval, J.A.; Alonso, F.J.; Márquez, J. Glutaminase isoenzymes as key regulators in metabolic and oxidative stress against cancer. Curr. Mol. Med.,  2013, 13(4), 514-534.
 [http://dx.doi.org/10.2174/1566524011313040005] [PMID: 22934847]

[34]
Yang, S.; Lian, G. ROS and diseases: Role in metabolism and energy supply. Mol. Cell. Biochem.,  2020, 467(1-2), 1-12.
 [http://dx.doi.org/10.1007/s11010-019-03667-9] [PMID: 31813106]

[35]
Yang, T.; Tian, Y.; Yang, Y.; Tang, M.; Shi, M.; Chen, Y.; Yang, Z.; Chen, L. Design, synthesis, and pharmacological evaluation of 2-(1-(1,3,4-thiadiazol-2-yl)piperidin-4-yl)ethan-1-ol analogs as novel glutaminase 1 inhibitors. Eur. J. Med. Chem.,  2022, 243, 114686.
 [http://dx.doi.org/10.1016/j.ejmech.2022.114686] [PMID: 36055003]

[36]
Janicka, M.; Śliwińska, A. Quantitative retention (structure)–activity relationships in predicting the pharmaceutical and toxic properties of potential pesticides. Molecules,  2022, 27(11), 3599.
 [http://dx.doi.org/10.3390/molecules27113599] [PMID: 35684533]

[37]
Evans, D.A. History of the harvard chemdraw project. Angew. Chem. Int. Ed.,  2014, 53(42), 11140-11145.
 [http://dx.doi.org/10.1002/anie.201405820] [PMID: 25131311]

[38]
Froimowitz, M. HyperChem: A software package for computational chemistry and molecular modeling. Biotechniques,  1993, 14(6), 1010-1013.
 [PMID: 8333944]

[39]
Katritzky, A.R.; Perumal, S.; Petrukhin, R.; Kleinpeter, E. Codessa-based theoretical QSPR model for hydantoin HPLC-RT lipophilicities. J. Chem. Inf. Comput. Sci.,  2001, 41(3), 569-574.
 [http://dx.doi.org/10.1021/ci000099t] [PMID: 11410031]

[40]
Allen, A. The cardiotoxicity of chemotherapeutic drugs. Semin. Oncol.,  1992, 19(5), 529-542.
 [PMID: 1411651]

[41]
Teodorescu, L.; Sherwood, D. High energy physics event selection with gene expression programming. Comput. Phys. Commun.,  2008, 178(6), 409-419.
 [http://dx.doi.org/10.1016/j.cpc.2007.10.003]

[42]
Kaydani, H.; Mohebbi, A.; Eftekhari, M. Permeability estimation in heterogeneous oil reservoirs by multi-gene genetic programming algorithm. J. Petrol. Sci. Eng.,  2014, 123, 201-206.
 [http://dx.doi.org/10.1016/j.petrol.2014.07.035]

[43]
Gharagheizi, F.; Ilani-Kashkouli, P.; Farahani, N.; Mohammadi, A.H. Gene expression programming strategy for estimation of flash point temperature of non-electrolyte organic compounds. Fluid Phase Equilib.,  2012, 329, 71-77.
 [http://dx.doi.org/10.1016/j.fluid.2012.05.015]

[44]
Yu, Z.; Li, X.; Ge, C.; Si, H.; Cui, L.; Gao, H.; Duan, Y.; Zhai, H. 3D-QSAR modeling and molecular docking study on Mer kinase inhibitors of pyridine-substituted pyrimidines. Mol. Divers.,  2015, 19(1), 135-147.
 [http://dx.doi.org/10.1007/s11030-014-9556-0] [PMID: 25355276]

[45]
Patel, P.D.; Patel, M.R.; Kaushik-Basu, N.; Talele, T.T. 3D QSAR and molecular docking studies of benzimidazole derivatives as hepatitis C virus NS5B polymerase inhibitors. J. Chem. Inf. Model.,  2008, 48(1), 42-55.
 [http://dx.doi.org/10.1021/ci700266z] [PMID: 18076152]

[46]
Ai, Y.; Wang, S.T.; Tang, C.; Sun, P.H.; Song, F.J. 3D-QSAR and docking studies on pyridopyrazinones as BRAF inhibitors. Med. Chem. Res.,  2011, 20(8), 1298-1317.
 [http://dx.doi.org/10.1007/s00044-010-9468-1]

[47]
Li, X.; Ye, L.; Wang, X.; Wang, X.; Liu, H.; Qian, X.; Zhu, Y.; Yu, H. Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls. Sci. Total Environ.,  2012, 441, 230-238.
 [http://dx.doi.org/10.1016/j.scitotenv.2012.08.072] [PMID: 23137989]

[48]
Hadni, H.; Elhallaoui, M. 2D and 3D-QSAR, molecular docking and ADMET properties in silico studies of azaaurones as antimalarial agents. New J. Chem.,  2020, 44(16), 6553-6565.
 [http://dx.doi.org/10.1039/C9NJ05767F]

[49]
Yan, W.; Lin, G.; Zhang, R.; Liang, Z.; Wu, W. Studies on the bioactivities and molecular mechanism of antioxidant peptides by 3D-QSAR, in vitro evaluation and molecular dynamic simulations. Food Funct.,  2020, 11(4), 3043-3052.
 [http://dx.doi.org/10.1039/C9FO03018B] [PMID: 32190865]

[50]
Yang, Y.; Qin, J.; Liu, H.; Yao, X. Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors. J. Chem. Inf. Model.,  2011, 51(3), 680-692.
 [http://dx.doi.org/10.1021/ci100427j] [PMID: 21338122]

[51]
Mouchlis, V.D.; Melagraki, G.; Mavromoustakos, T.; Kollias, G.; Afantitis, A. Molecular modeling on pyrimidine-urea inhibitors of TNF-α production: An integrated approach using a combination of molecular docking, classification techniques, and 3D-QSAR CoMSIA. J. Chem. Inf. Model.,  2012, 52(3), 711-723.
 [http://dx.doi.org/10.1021/ci200579f] [PMID: 22360289]

[52]
Mao, Y.; Li, Y.; Hao, M.; Zhang, S.; Ai, C. Docking, molecular dynamics and quantitative structure-activity relationship studies for HEPTs and DABOs as HIV-1 reverse transcriptase inhibitors. J. Mol. Model.,  2012, 18(5), 2185-2198.
 [http://dx.doi.org/10.1007/s00894-011-1236-8] [PMID: 21947448]

[53]
Damiani, C.; Colombo, R.; Gaglio, D.; Mastroianni, F.; Pescini, D.; Westerhoff, H.V.; Mauri, G.; Vanoni, M.; Alberghina, L. A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect. PLOS Comput. Biol.,  2017, 13(9), e1005758.
 [http://dx.doi.org/10.1371/journal.pcbi.1005758] [PMID: 28957320]

[54]
Luengo, A.; Gui, D.Y.; Vander Heiden, M.G. Targeting metabolism for cancer therapy. Cell Chem. Biol.,  2017, 24(9), 1161-1180.
 [http://dx.doi.org/10.1016/j.chembiol.2017.08.028] [PMID: 28938091]

[55]
Wang, Z.; Liu, F.; Fan, N.; Zhou, C.; Li, D.; Macvicar, T.; Dong, Q.; Bruns, C.J.; Zhao, Y. Targeting glutaminolysis: New perspectives to understand cancer development and novel strategies for potential target therapies. Front. Oncol.,  2020, 10, 589508.
 [http://dx.doi.org/10.3389/fonc.2020.589508] [PMID: 33194749]

[56]
DeBerardinis, R.J.; Mancuso, A.; Daikhin, E.; Nissim, I.; Yudkoff, M.; Wehrli, S.; Thompson, C.B. Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl. Acad. Sci.,  2007, 104(49), 19345-19350.
 [http://dx.doi.org/10.1073/pnas.0709747104] [PMID: 18032601]

[57]
Fu, Q.; Xu, L.; Wang, Y.; Jiang, Q.; Liu, Z.; Zhang, J.; Zhou, Q.; Zeng, H.; Tong, S.; Wang, T.; Qi, Y.; Hu, B.; Fu, H.; Xie, H.; Zhou, L.; Chang, Y.; Zhu, Y.; Dai, B.; Zhang, W.; Xu, J. Tumor-associated macrophage-derived interleukin-23 interlinks kidney cancer glutamine addiction with immune evasion. Eur. Urol.,  2019, 75(5), 752-763.
 [http://dx.doi.org/10.1016/j.eururo.2018.09.030] [PMID: 30293904]

[58]
Schmidt, D.R.; Patel, R.; Kirsch, D.G.; Lewis, C.A.; Vander Heiden, M.G.; Locasale, J.W. Metabolomics in cancer research and emerging applications in clinical oncology. CA Cancer J. Clin.,  2021, 71(4), 333-358.
 [http://dx.doi.org/10.3322/caac.21670] [PMID: 33982817]

[59]
Bott, A.J.; Shen, J.; Tonelli, C.; Zhan, L.; Sivaram, N.; Jiang, Y.P.; Yu, X.; Bhatt, V.; Chiles, E.; Zhong, H.; Maimouni, S.; Dai, W.; Velasquez, S.; Pan, J.A.; Muthalagu, N.; Morton, J.; Anthony, T.G.; Feng, H.; Lamers, W.H.; Murphy, D.J.; Guo, J.Y.; Jin, J.; Crawford, H.C.; Zhang, L.; White, E.; Lin, R.Z.; Su, X.; Tuveson, D.A.; Zong, W.X. Glutamine anabolism plays a critical role in pancreatic cancer by coupling carbon and nitrogen metabolism. Cell Rep.,  2019, 29(5), 1287-1298.e6.
 [http://dx.doi.org/10.1016/j.celrep.2019.09.056] [PMID: 31665640]

[60]
Li, X.; Liu, M.; Liu, H.; Chen, J. Tumor metabolic reprogramming in lung cancer progression (Review). Oncol. Lett.,  2022, 24(2), 287.

[61]
Mukha, A.; Kahya, U.; Linge, A.; Chen, O.; Löck, S.; Lukiyanchuk, V.; Richter, S.; Alves, T.C.; Peitzsch, M.; Telychko, V.; Skvortsov, S.; Negro, G.; Aschenbrenner, B.; Skvortsova, I.I.; Mirtschink, P.; Lohaus, F.; Hölscher, T.; Neubauer, H.; Rivandi, M.; Labitzky, V.; Lange, T.; Franken, A.; Behrens, B.; Stoecklein, N.H.; Toma, M.; Sommer, U.; Zschaeck, S.; Rehm, M.; Eisenhofer, G.; Schwager, C.; Abdollahi, A.; Groeben, C.; Kunz-Schughart, L.A.; Baretton, G.B.; Baumann, M.; Krause, M.; Peitzsch, C.; Dubrovska, A. GLS-driven glutamine catabolism contributes to prostate cancer radiosensitivity by regulating the redox state, stemness and ATG5-mediated autophagy. Theranostics,  2021, 11(16), 7844-7868.
 [http://dx.doi.org/10.7150/thno.58655] [PMID: 34335968]

[62]
Ma, G.; Zhang, Z.; Li, P.; Zhang, Z.; Zeng, M.; Liang, Z.; Li, D.; Wang, L.; Chen, Y.; Liang, Y.; Niu, H. Reprogramming of glutamine metabolism and its impact on immune response in the tumor microenvironment. Cell Commun. Signal.,  2022, 20(1), 114.
 [http://dx.doi.org/10.1186/s12964-022-00909-0] [PMID: 35897036]

[63]
Ramachandran, S.; Pan, C.Q.; Zimmermann, S.C.; Duvall, B.; Tsukamoto, T.; Low, B.C.; Sivaraman, J. Structural basis for exploring the allosteric inhibition of human kidney type glutaminase. Oncotarget,  2016, 7(36), 57943-57954.
 [http://dx.doi.org/10.18632/oncotarget.10791] [PMID: 27462863]

[64]
Leone, R.D.; Zhao, L.; Englert, J.M.; Sun, I.M.; Oh, M.H.; Sun, I.H.; Arwood, M.L.; Bettencourt, I.A.; Patel, C.H.; Wen, J.; Tam, A.; Blosser, R.L.; Prchalova, E.; Alt, J.; Rais, R.; Slusher, B.S.; Powell, J.D. Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion. Science,  2019, 366(6468), 1013-1021.
 [http://dx.doi.org/10.1126/science.aav2588] [PMID: 31699883]

[65]
Thangavelu, K.; Pan, C.Q.; Karlberg, T.; Balaji, G.; Uttamchandani, M.; Suresh, V.; Schüler, H.; Low, B.C.; Sivaraman, J. Structural basis for the allosteric inhibitory mechanism of human kidney-type glutaminase (KGA) and its regulation by Raf-Mek-Erk signaling in cancer cell metabolism. Proc. Natl. Acad. Sci.,  2012, 109(20), 7705-7710.
 [http://dx.doi.org/10.1073/pnas.1116573109] [PMID: 22538822]

[66]
Rashdan, H.R.M.; Farag, M.M.; El-Gendey, M.S.; Mounier, M.M. Toward rational design of novel anti-cancer drugs based on targeting, solubility, and bioavailability exemplified by 1,3,4-thiadiazole derivatives synthesized under solvent-free conditions. Molecules,  2019, 24(13), 2371.
 [http://dx.doi.org/10.3390/molecules24132371] [PMID: 31252614]

[67]
Surov, A.O.; Volkova, T.V.; Churakov, A.V.; Proshin, A.N.; Terekhova, I.V.; Perlovich, G.L. Cocrystal formation, crystal structure, solubility and permeability studies for novel 1,2,4-thiadiazole derivative as a potent neuroprotector. Eur. J. Pharm. Sci.,  2017, 109, 31-39.
 [http://dx.doi.org/10.1016/j.ejps.2017.07.025] [PMID: 28756204]

Rights & Permissions Print Cite

Article Metrics

22

2

Journal Information

For Authors

For Editors

For Reviewers

Explore Articles

Open Access

Open Access Articles

For Visitors

DOI https://dx.doi.org/10.2174/1570180820666230901162718	Print ISSN 1570-1808
Publisher Name Bentham Science Publisher	Online ISSN 1875-628X

Letters in Drug Design & Discovery

Conducting 2D and 3D QSAR Analyses and Molecular Docking Studies of Analogues of 2-(1-(1,3,4-thiadiazol-2-yl)piperidin-4-yl)ethan-1-ol with the Aim of Identifying Promising Drug Candidates for Targeting Glioblastoma

Abstract

Graphical Abstract

Related Journals

Related Books

Related Articles