: 40-47
Received: August 09, 2023
Revised: September 01, 2023
Accepted: September 12, 2023
Department of Chemistry and Biochemistry, Department of Physics, Concordia University

This paper focused on a new application of the TOPSIS method for the prediction and optimization of the oligonucleotides characteristics. This method has been used for these purposes as it has shown its efficacy for these analyses. This is the first time that it has been applied to the investigation of these biomolecules. The hypothesis in this paper was that the characteristics of these biomaterials would be optimized according to their structural differences. The obtained results showed that the stabilization of oligonucleotides would affect their ranking with TOPSIS when the stability of these biomolecules increased against enzymes in their structure. In other words, the oligonucleotides with less enzymatic degradation were ranked better with this method. This study showed the first application of this algorithm for the prediction and optimization of the oligonucleotides’ characteristics. The results in this work revealed that the ranks of candidates depended on their distances from their ideal solutions. This showed that TOPSIS could be used as an appropriate method in the optimization of oligonucleotides as the rankings with this method would coincide with the data that concern the stability of these biomolecules against enzymatic degradation. The results of this work could be applied for the preparation of novel materials with applications in science and engineering.

[1] Binder, H., Preibisch, S. Specific and nonspecific hybridization of oligonucleotide probes on microarrays, Biophys. J., vol. 89, pp. 337-352, 2005.
[2] Iyer, M. et al. Accelerated hybridization of oligonucleotides to duplex DNA, J. Biol. Chem., vol. 270, pp. 14712-14717, 1995.
[3] Juskowiak, B., Nucleic acid-based fluorescent probes and their analytical potential, Anal. Bioanal. Chem., vol. 399, pp. 3157-3176, 2011.
[4] Waminal, N.E. et al., Rapid and efficient FISH using pre-labeled oligomer probes, Scientific Reports, 8224, 2018.
[5] Rukov, J.L. et al. Dissecting the target specificity of RNase H recruiting oligonucleotides using massively parallel reporter analysis of short RNA motifs, Nucleic Acids Res., vol. 43, pp. 8476-8487, 2015.
[6] Lai, F., et al. Directed RNase H cleavage of nascent transcripts causes transcription termination, Molecular Cell, vol. 77, pp. 1032-1043, 2020.
[7] Vickers, T.A., Crooke, S.T. Antisense oligonucleotides capable of promoting specific target mRNA reduction via competing RNase H1-dependent and independent mechanisms, Plos One, 2014.
[8] Lee, J.E. et al. RNase H-mediated degradation of toxic RNA in myotonic dystrophy type 1, Proceedings of the National Academy of Sciences, vol. 109, pp. 4221-4226, 2012.
[9] Dallavalle, S. et al. Improvement of conventional anti-cancer drugs as new tools against multidrug resistant tumors, Drug Resistance Uptakes, vol. 50, 100682, 2020.
[10] Emran, T.B. et al. Multidrug resistance in cancer: Understanding molecular mechanisms, immunoprevention and therapeutic approaches, Frontiers, Sec. Pharmacology of Anti-Cancer Drugs, 2022.
[11] Vaidya, F.U. et al. Molecular and cellular paradigms of multidrug resistance in cancer, Cancer Reports, e1291, 2020.
[12] Fojo, A.T. et al.  Expression of a multidrug-resistance gene in human tumors and tissues, Proc. Natl. Acad. Sci., vol. 84, pp. 265-269, 1987.
[13] Roninson, I.B. The role of MDR1 (P-glycoprotein) gene in multidrug resistance in vitro and in vivo, Biochem. Pharmacol., vol. 43, pp. 95-102, 1992.
[14] Ling, V.  P-glycoprotein and resistance to anticancer drugs, Cancer, vol. 69, pp. 2603-2609, 1992.
[15] Choong, E. The permeability P-glycoprotein: a focus on enantioselectivity and brain distribution, Expert Opin. Drug Metab. Toxicol., vol. 6, pp. 953-65, 2010.
[16] Djavanbakht Samani, T., Jolles, B., Laigle, A. Best minimally modified antisense oligonucleotides according to cell nuclease activity, Antisense and Nucleic Acid Drug Development, vol. 11, pp. 129-136 2001.
[17] Brigui, I., Djavanbakht Samani, T., Jollès, B., Laigle, A. Minimally modified phosphodiester antisense oligodeoxyribonucleotide directed against the multidrug resistance gene mdr1, Biochem. Pharmacol., vol. 65, pp. 747-54, 2003.
[18] Whitesell, L. et al. Stability, clearance, and disposition of intraventricularly administered oligodeoxynucleotides: Implications for therapeutic application within the central nervous system, Proc. Natl. Acad. Sci., vol. 90, pp. 4665-4669, 1993.
[19] Culman, J. Antisense oligonucleotides in the study of central mechanisms of the cardiovascular regulation, Exp.Physiol., vol. 85, pp. 757-767, 2000.
[20] Wojcik, M. et al. Nucleotide pyrophosphatase/phosphodiesterase 1 Is responsible for degradation of antisense phosphorothioate oligonucleotides, Oligonucleotides, vol. 17, pp. 134-45, 2007.
[21] Kanazaki, M. et al. Highly nuclease-resistant phosphodiester-type oligodeoxynucleotides containing 4'α-C-aminoalkylthymidines form thermally stable duplexes with DNA and RNA. A candidate for potent antisense molecules, J. Am. Chem. Soc., vol. 122, pp. 2422-2432, 2000.
[22] Jahrsdörfer, B. et al. Phosphorothyoate oligodeoxynucleotides block nonspecific binding of Cy5 conjugates to monocytes,  J. Immunol. Methods., vol. 297, pp. 259-263, 2005.
[23] Hatta, T. et al. Phosphorothioate oligonucleotides block reverse transcription by the RNase-H activity associated with the HIV-1 polymerase, Biochemical and Biophysical Research Communications, vol. 211, pp. 1041-1046, 1995.
[24] Javanbakht, T., Chakravorty, S. Prediction of human behavior with TOPSIS. Fuzzy Extension and Applications, vol. 3, pp. 109-125.
[25] Javanbakht, T., Chakravorty, S. Optimization of machine learning algorithms for proteomic analysis using TOPSIS, Journal of Engineering Sciences, vol. 9, pp. E7-E12, 2022.
[26] Balioti,  V., Tzimopoulos,  C., Evangelides, C. Multi-criteria decision making using TOPSIS method under fuzzy environment. Application in spillway selection, Proceedings, vol. 2, 637, 2018.
[27] Bulgurcu, B. Application of TOPSIS technique for financial performance evaluation of technology firms in Istanbul stock exchange market, Procedia, vol. 62, pp. 1033-1040, 2012.
[28] Wang, J. et al. Adsorption of DNA Oligonucleotides by Self-Assembled Metalloporphyrin Nanomaterials, Langmuir, 38, vol. 11, pp. 3553-3560, 2022.
[29] Kim, J. et al. Advances in intracellular delivery through supramolecular self-assembly of oligonucleotides and peptides, Theranostics, vol. 9, 3191-3212, 2019.
[30] Sahle, F.F., Lowe, T.L. Design strategies for programmable oligonucleotide nanotherapeutics, Drug Discov Today, vol. 25, 73-88, 2020.
[31] Wei, M. et al. Polyvalent immunostimulatory nanoagents with self-assembled CpG oligonucleotide-conjugated gold nanoparticle, Angewandte Chemie, vol. 51, pp. 1202-1206, 2011.
[32] Maccullock, T. et al. Emerging applications of peptide-oligonucleotide conjugates: bioactive scaffolds, self-assembling systems, and hybrid nanomaterialsm, Organic and Biomolecular Chemistry, vol. 17, pp. 1668-1682, 2019.
[33] Javanbakht, T. et al. Correlation between physicochemical properties of superparamagnetic iron oxide nanoparticles and their reactivity with hydrogen peroxide, Canadian Journal of Chemistry, vol. 98, pp. 601-608, 2020.
[34] Javanbakht, T. Ghane-Motlagh, B., Sawan, M. Comparative study of antibiofilm activity and physicochemical properties of microelectrode arrays, Microelectronic Engineering, vol. 229, 111305, 2020.
[35] Da Pieve, F. Physicochemical properties and complexity of amino acids beyond our biosphere: Analysis of the isoleucine group from meteorites, ACS Earth Space Chem., vol. 3, pp. 1955-1965, 2019.
[36] Djavanbakht, T. et al. Effets d'un chauffage thermique sur les performances de miroirs multicouches Mo/Si, Mo/C et Ni/C pour le rayonnement X mou, J. Phys. IV France, vol. 10, pp. 281-287, 2000.
[37] Gatoo, M.A. et al. Physicochemical properties of nanomaterials: Implication in associated toxic manifestations, BioMed Research International, vol. 2014, 498420, 2014.
[38] Javanbakht, T., David, E. Rheological and physical properties of a nanocomposite of graphene oxide nanoribbons with polyvinyl alcohol, Journal of Thermoplastic Composite Materials, vol. 35, pp. 651-664, 2020.
[39] Javanbakht, T. Investigation of rheological properties of graphene oxide and its nanocomposite with polyvinyl alcohol, Ukrainian Journal of Mechanical Engineering and Materials Science, vol. 7, pp. 23-32, 2021.
[40] Javanbakht, T. et al. Related physicochemical, rheological, and dielectric properties of nanocomposites of superparamagnetic iron oxide nanoparticles with polyethyleneglycol, Journal of Applied Polymer Science, vol. 136, 48280-48290, 2019.
[41] Farooq, F. et al. Experimental investigation of hybrid carbon nanotubes and graphite nanoplatelets on rheology, shrinkage, mechanical, and microstructure of SCCM, Materials, vol. 13, 230, 2020.
[42] Javanbakht, T., Sokolowski, W. Thiol-ene/acrylate systems for biomedical shape-memory polymers, Shape Memory Polymers for Biomedical Applications, pp. 157-166, 2015.
[43] Patil-Sen, Y. Advances in nano-biomaterials and their applications in biomedicine, Emerg Top Life Sci.,  vol. 14, pp. 169-176, 2021.
[44] Feng, J.-J. et al. Biocompatible functional nanomaterials: Synthesis, properties, and applications, Journal of Nanomaterials, vol. 2013, 385939, 2013.
[45] Javanbakht, T., Hadian, H., Wilkinson, K.J. Comparative study of physicochemical properties and antibiofilm activity of graphene oxide nanoribbons, Journal of Engineering Sciences, wol. 7, pp. C1-C8, 2020.
[46] Bezerra, D.M., Assaf, E.M. Influence of the preparation method on the structural properties of mixed metal oxides, Science and Technology of Materials, vol. 30, pp. 166-173, 2018.
[47] Ishihara, K. et al. Preparation of phospholipid polymers and their properties as polymer hydrogel membranes, Polymer Journal, vol. 22, pp. 355-360, 1990.
[48] Jadhav, P.S. et al. Study of the preparation and properties of polyvinyl chloride/nitrocellulose polymer blends, Polymer International, vol. 71, 1009-1021, 2022.
[49] Saini K; Preparation method, Properties and Crosslinking of hydrogel: A review, Pharma Tutor, vol. 5, pp. 27-36, 2017.
[50] Al-Muhtaseb, S.A., Ritter, J.A. Preparation and properties of resorcinol-formaldehyde organic and carbon gels, Advanced Materials, vol. 15, pp. 101-114, 2003.
[51] Varatharajulu, M. et al. Multi criteria decision making through TOPSIS and COPRAS on drilling parameters of magnesium AZ91, Journal of Magnesium and Alloys, Vol. 10, pp. 2857-2874, 2022.
[52] Shukla, A. et al. Applications of TOPSIS algorithm on various manufacturing processes: A review, Materials Today: Proceedings, vol. 4, pp. 5320-5329, 2017.
[53] Kazi, F.M. et al. Multi-objective optimization of the aluminum powder-mixed EDM process using the GRA and TOPSIS techniques based on the fuzzy AHP approach, Journal of applied research and technology, vol. 19, 2022.
[54] Hanine, M. et al. Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection, Springer Plus, 263, 2016.
[55] Javanbakht, T. A novel automated decision-making process for analysis of ions and organic materials in drinking water, J. Eng. Sci., vol. 10, pp. H1-H7, 2023.
[56] Darji, V.P., Rao, R.V. Application of AHP/EVAMIX method for decision making in the industrial environment, American Journal of Operations Research, vol.3, 39747, 2013.
[57] Rafiee, R. et al. The optimum support selection by using fuzzy analytical hierarchy process method for Beheshtabad water transporting tunnel in Naien, Iranian Journal of Fuzzy Systems, vol. 10, pp. 39-51, 2013.
[58] Li, Y. et al. The research of applying TOPSIS combined with grey relational analysis approach for building energy consumption evaluation, Proceedings of the 8th International Symposium on Heating, Ventilation and Air Conditioning, pp. 611-619, 2013.
[59] Magableh, G.M., Mistarihi, M.Z. Applications of MCDM approach (ANP-TOPSIS) to evaluate supply chain solutions in the context of COVID-19, Heliyon, vol. 8, e09062, 2022.
[60] ArunRamnath, R., Thyla, P.R. Measurement and optimization of multi-attribute characteristics in milling epoxy granite composites using rsm and combined ahp-topsis, Surface Topography: Metrology and Properties, vol. 10, 025023, 2022.
[61] Huang, J. et al. Research on supply quantity transportation and ordering method based on TOPSIS and support vector regression,  Academic Journal of Business and Management, vol. 3, pp. 51-55, 2021.
[62] Yang, H. et al. Evaluation of DDOS attack degree based on GRA-TOPSIS model, International Conference on Smart Grid and Electrical Automation (ICSGEA), 2019.