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Research Articles

DFT based QSAR study on quinolone-triazole derivatives as antibacterial agents

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Pages 418-428 | Received 02 Aug 2021, Accepted 30 Sep 2021, Published online: 24 Oct 2021

References

  • Zhang J, Wang S, Ba Y, et al. 1,2,4-Triazole-quinoline/quinolone hybrids as potential anti-bacterial agents. Eur J Med Chem. 2019;174:1–8.
  • Ezelarab HAA, Abbas SH, Hassan HA, et al. Recent updates of fluoroquinolones as antibacterial agents. Arch Pharm Chem Life Sci. 2018;351(9):1800141.
  • Plech T, Kaproń B, Paneth A, et al. Determination of the primary molecular target of 1,2,4-triazole-ciprofloxacin hybrids . Molecules. 2015;20(4):6254–6272.
  • Xu JH, Fan YL, Zhou J. Quinolone–triazole hybrids and their biological activities. J Heterocyclic Chem. 2018;55(8):1854–1862.
  • Chu X-M, Wang C, Wang W-L, et al. Triazole derivatives and their antiplasmodial and antimalarial activities. Eur J Med Chem. 2019;166:206–223.
  • Gao F, Wang T, Xiao J, et al. Antibacterial activity study of 1,2,4-triazole derivatives. Eur J Med Chem. 2019;173:274–281.
  • Zhang B. Comprehensive review on the anti-bacterial activity of 1,2,3-triazole hybrids. Eur J Med Chem. 2019;168:357–372.
  • Plech T, Wujec M, Kosikowska U, et al. Synthesis and in vitro activity of 1,2,4-triazole-ciprofloxacin hybrids against drug-susceptible and drug-resistant bacteria. Eur J Med Chem. 2013;60:128–134.
  • Ceylan S, Bayrak H, Ozdemir SB, et al. Microwave-assisted and conventional synthesis of novel antimicrobial 1, 2, 4-triazole derivatives containing nalidixic acid skeleton. Heterocyclic Commun. 2016;22(4):229–237.
  • Kant R, Singh V, Nath G, et al. Design, synthesis and biological evaluation of ciprofloxacin tethered bis-1,2,3-triazole conjugates as potent antibacterial agents. Eur J Med Chem. 2016;124:218–228.
  • Popiołek Ł, Biernasiuk A, Paruch K, et al. Synthesis and in vitro antimicrobial activity screening of new pipemidic acid derivatives. Arch Pharm Res. 2018;41(6):633–645.
  • Ketabi S, Haeri HH, Hashemianzadeh SM. Solvation free energies of glutamate and its metal complexes: a computer simulation study. J Mol Model. 2011;17(4):889–898.
  • Haeri HH, Ketabi S, Hashemianzadeh SM. The solvation study of carbon, silicon and their mixed nanotubes in water solution. J Mol Model. 2012;18(7):3379–3388.
  • Ketabi S, Hashemianzadeh SM, MoghimiWaskasi M. Study of DNA base-Li doped SiC nanotubes in aqueous solutions: a computer simulation study. J Mol Model. 2013;19(4):1605–1615.
  • Ketabi S, Rahmani L. Carbon nanotube as a carrier in drug delivery system for carnosine dipeptide: a computer simulation study. Mater Sci Eng C Mater Biol Appl. 2017;73:173–181.
  • Khedkar VM, Ambre PK, Verma J, et al. Molecular docking and 3D-QSAR studies of HIV-1 protease inhibitors. J Mol Model. 2010;16(7):1251–1268.
  • Zhu J, Ke K, Xu L, et al. Theoretical studies on the selectivity mechanisms of PI3Kδ inhibition with marketed idelalisib and its derivatives by 3D-QSAR, molecular docking, and molecular dynamics simulation. J Mol Model. 2019;25(8):242.
  • Patel HM, Noolvi MN, Sharma P, et al. Quantitative structure–activity relationship (QSAR) studies as strategic approach in drug discovery. Med Chem Res. 2014;23(12):4991–5007.
  • Eroğlu E. DFT-based QSAR modelling of selectivity and inhibitory activity of coumarins and sulfocoumarins against tumor-associated carbonic anhydrase isoform IX. Comput Biol Chem. 2019;80:307–313.
  • Ahmadi S. Mathematical modeling of cytotoxicity of metal oxide nanoparticles using the index of ideality correlation criteria. Chemosphere. 2020;242:125192.
  • Ahmadi S, Ghanbari H, Lotfi S, et al. Predictive QSAR modeling for the antioxidant activity of natural compounds derivatives based on Monte Carlo method. Mol Divers. 2021;25(1):87–11.
  • Lotfi S, Ahmadi S, Zohrabi P. QSAR modeling of toxicities of ionic liquids toward Staphylococcus aureus using SMILES and graph invariants. Struct Chem. 2020;31(6):2257–2214.
  • Ahmadi S, Akbari A. Prediction of the adsorption coefficients of some aromatic compounds on multi-wall carbon nanotubes by the Monte Carlo method. SAR QSAR Environ Res. 2018;29(11):895–909.
  • Ahmadi S, Mardinia F, Azimi N, et al. Prediction of chalcone derivative cytotoxicity activity against MCF-7 human breast cancer cell by Monte Carlo method. J Mol Struct. 2019;1181:305–311.
  • Ahmadi S, Toropova AP, Toropov AA. Correlation intensity index: mathematical modeling of cytotoxicity of metal oxide nanoparticles. Nanotoxicology. 2020;14(8):1118–1119.
  • Javidfar M, Ahmadi S. QSAR modelling of larvicidal phytocompounds against Aedes aegypti using index of ideality of correlation. SAR QSAR Environ Res. 2020;31(10):717–739.
  • Zhao X, Zhao Y, Ren Z, et al. Combined QSAR/QSPR and molecular docking study on fluoroquinolones to reduce biological enrichment. Comput Biol Chem. 2019;79:177–184.
  • Estrada E, Uriarte E. Recent advances on the role of topological indices in drug discovery research. Curr Med Chem. 2001;8(13):1573–1588.
  • Wong KY, Mercader AG, Saavedra LM, et al. QSAR analysis on tacrine-related acetylcholinesterase inhibitors. J Biomed Sci. 2014;21(1):84.
  • Faidallah HM, Girgis AS, Tiwari AD, et al. Synthesis, antibacterial properties and 2D-QSAR studies of quinolone-triazole conjugates. Eur J Med Chem. 2018;143:1524–1534.
  • Cui S-F, Ren Y, Zhang S-L, et al. Synthesis and biological evaluation of a class of quinolone triazoles as potential antimicrobial agents and their interactions with calf thymus DNA. Bioorg Med Chem Lett. 2013;23(11):3267–3272.
  • Wang Y, Damu GLV, Lv J-S, et al. Design, synthesis and evaluation of clinafloxacin triazole hybrids as a new type of antibacterial and antifungal agents. Bioorg Med Chem Lett. 2012;22(17):5363–5366.
  • Wikler MA. Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically: approved standard. CLSI (NCCLS). 2006;26:M7–A7.
  • Schmidt MW, Baldridge KK, Boatz JA, et al. General atomic and molecular electronic structure system. J Comput Chem. 1993;14(11):1347–1363.
  • Pearson RG. Absolute electronegativity and absolute hardness of Lewis acids and bases. J Am Chem Soc. 1985;107(24):6801–6806.
  • Sastri VS, Perumareddi JR. Molecular orbital theoretical studies of some organic corrosion inhibitors. Corrosion. 1997;53(8):617–622.
  • Leonard JT, Roy K. On selection of training and test sets for the development of predictive QSAR models. QSAR Comb Sci. 2006;25(3):235–251.
  • Andrada MF, Vega-Hissi EG, Estrada MR, et al. Impact assessment of the rational selection of training and test sets on the predictive ability of QSAR models. SAR QSAR Environ Res. 2017;28(12):1011–1023.
  • Golbraikh A, Shen M, Xiao Z, et al. Rational selection of training and test sets for the development of validated QSAR models. J Comput Aided Mol Des. 2003;17(2-4):241–253.
  • Yim O, Ramdeen KT. Hierarchical cluster analysis: comparison of three linkage measures and application to psychological data. TQMP. 2015;11(1):8–21.
  • Field A. Discovering statistics using IBM SPSS statistics. London: Sage; 2013.
  • Ghani IMM, Ahmad S. Stepwise multiple regression method to forecast fish landing. Proc-Soc Behav Sci. 2010;8:549–554.
  • Gramatica P. Principles of QSAR models validation: internal and external. QSAR Comb Sci. 2007;26(5):694–701.
  • Hawkins DM, Basak SC, Mills D. Assessing model fit by cross-validation. J Chem Inf Comput Sci. 2003;43(2):579–586.
  • Rücker C, Rücker G, Meringer M. y-Randomization and its variants in QSPR/QSAR. J Chem Inf Model. 2007;47(6):2345–2357.
  • Chirico N, Gramatica P. Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient. J Chem Inf Model. 2011;51(9):2320–2335.
  • Roy K, Kar S, Ambure P. On a simple approach for determining applicability domain of QSAR models. Chemometrics Intell Lab Syst. 2015;145:22–29.
  • Chirico N, Gramatica P. Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection. J Chem Inf Model. 2012;52(8):2044–2058.
  • Todeschini R, Consonni V. Handbook of molecular descriptors. Vol. 11. New York: John Wiley & Sons; 2008.
  • Karelson M, Lobanov VS, Katritzky AR. Quantum-chemical descriptors in QSAR/QSPR studies. Chem Rev. 1996;96(3):1027–1044.
  • Shabaan AKE, Hassan AE, Saadullah GA. Of protonation and deprotonation on the reactivity of quinolone: a theoretical study. Chin Sci Bull. 2012;57(14):1665–1671.
  • Verma RP, Hansch C. Use of 13C NMR chemical shift as QSAR/QSPR descriptor. Chem Rev. 2011;111(4):2865–2899.
  • Singh S, Singh J, Ingle M, et al. A QSAR study on carbonic anhydrase inhibition: predicting logKi (hCAI) by using (SO2NH2) NMR chemical shift as a molecular descriptor. ARKIVOC. 2006;2006(16):1–15.
  • Khan AU. Descriptors and their selection methods in QSAR analysis: paradigm for drug design. Drug Discov Today. 2016;21(8):1291–1302.
  • Kujawski J, Popielarska H, Myka A, et al. The log P parameter as a molecular descriptor in the computer-aided drug design–an overview. CMST. 2012;18(2):81–88.
  • Henwood JM, Monk JP. Enoxacin. A review of its antibacterial activity, pharmacokinetic properties and therapeutic useDrugs. 1988;36(1):32–66.
  • Mentese M, Demirbas N, Mermer A, et al. Novel azole-functionalited flouroquinolone hybrids: design, conventional and microwave irradiated synthesis, evaluation as antibacterial and antioxidant agents. LDDD. 2018;15(1):46–64.

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