Quantitative Structure–Property Relationship Analysis in Molecular Graphs of Some Anticancer Drugs with Temperature Indices Approach
Abstract
:1. Introduction
2. Preliminaries
3. Results
- index;
- index;
- index;
- index;
- index.
4. Temperature Indices and QSPR
Regression Models
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Ghorbani, M.; Hosseinzadeh, M.A. A new version of Zagreb indices. Filomat 2012, 26, 93–100. [Google Scholar] [CrossRef]
- Hayat, S.; Suhaili, N.; Jamil, H. Statistical significance of valency-based topological descriptors for correlating thermodynamic properties of benzenoid hydrocarbons with applications. Comput. Theor. Chem. 2023, 1227, 114259. [Google Scholar] [CrossRef]
- Kulli, V.R.; Pal, M.; Samanta, S.; Pal, A. Handbook of Research of Advanced Applications of Graph Theory in Modern Society; IGI Global: Hershey, PA, USA, 2020. [Google Scholar]
- Ghods, M.; Ramezani Tousi, J. Computing Revan Polynomials and Revan Indices of Copper (I) Oxide and Copper (II) Oxide. Commun. Comb. Cryptogr. Comput. Sci. 2021, 1, 50–58. [Google Scholar]
- Kosari, S. On spectral radius and Zagreb Estrada index of graphs. Asian-Eur. J. Math. 2023, 16, 2350176. [Google Scholar] [CrossRef]
- Kosari, S.; Dehgardi, N.; Khan, A. Lower bound on the KG-Sombor index. Commun. Comb. Optim. 2023, 8, 751–757. [Google Scholar]
- Ramezani Tousi, J.; Ghods, M. Computing K Banhatti and K Hyper Banhatti Indices of Titania Nanotubes TiO2[m, n]. J. Inf. Optim. Sci. (JIOS) 2023, 44, 207–216. [Google Scholar]
- Ramezani Tousi, J.; Ghods, M. Investigating Banhatti indices on the molecular graph and the line graph of Glass with M-polynomial approach. Proyecciones J. Math. 2024, 43, 199–219. [Google Scholar]
- Ramezani Tousi, J.; Ghods, M. Some polynomials and degree-based topological indices of molecular graph and line graph of Titanium dioxide nanotubes. J. Inf. Optim. Sci. 2024, 45, 95–106. [Google Scholar]
- Shi, X.; Kosari, S.; Hameed, S.; Shah, A.G.; Ullah, S. Application of connectivity index of cubic fuzzy graphs for identification of danger zones of tsunami threat. PLoS ONE 2024, 19, e0297197. [Google Scholar] [CrossRef]
- Lokesha, V.; Yasmeen, K.Z.V.L. Temperature Index of Certain Archimedean Lattice. South East Asian J. Math. Math. Sci. 2021, 17, 213. [Google Scholar]
- Adnan, M.; Bokhary, S.A.U.H.; Abbas, G.; Iqbal, T. Degree-based topological indices and QSPR analysis of antituberculosis drugs. J. Chem. 2022, 2022, 5748626. [Google Scholar] [CrossRef]
- Hayat, S.; Alanazi, S.J.; Liu, J.B. Two novel temperature-based topological indices with strong potential to predict physicochemical properties of polycyclic aromatic hydrocarbons with applications to silicon carbide nanotubes. Phys. Scr. 2024, 99, 055027. [Google Scholar] [CrossRef]
- Hayat, S.; Khan, A.; Ali, K.; Liu, J.B. Structure-property modeling for thermodynamic properties of benzenoid hydrocarbons by temperature-based topological indices. Ain Shams Eng. J. 2024, 15, 102586. [Google Scholar] [CrossRef]
- Hayat, S.; Liu, J.B. Comparative analysis of temperature-based graphical indices for correlating the total π-electron energy of benzenoid hydrocarbons. Int. J. Mod. Phys. B 2024, 2550047. [Google Scholar] [CrossRef]
- Havare, Ö.Ç. Quantitative structure analysis of some molecules in drugs used in the treatment of COVID-19 with topological indices. Polycycl. Aromat. Compd. 2022, 42, 5249–5260. [Google Scholar] [CrossRef]
- Huang, L.; Wang, Y.; Pattabiraman, K.; Danesh, P.; Siddiqui, M.K.; Cancan, M. Topological indices and QSPR modeling of new antiviral drugs for cancer treatment. Polycycl. Aromat. Compd. 2023, 43, 8147–8170. [Google Scholar] [CrossRef]
- Fajtolowicz, S. On conjectures of Graffitti. Discrete Math. 1988, 72, 113–118. [Google Scholar] [CrossRef]
- Kulli, V.R. Computation of Some Temperature Indices of HC5C5[p, q] Nanotubes. Ann. Pure Appl. Math. 2019, 20, 69–74. [Google Scholar] [CrossRef]
- Kulli, V.R. Temperature Sombor and temperature Nirmala indices. Int. J. Math. Comput. Res. (IJMCR) 2022, 10, 2910–2915. [Google Scholar] [CrossRef]
- Kansal, N.; Garg, P.; Singh, O. Temperature-based topological indices and QSPR Analysis of COVID-19 Drugs. Polycycl. Aromat. Compd. 2023, 43, 4148–4169. [Google Scholar] [CrossRef]
- Zhang, Y.; Khalid, A.; Siddiqui, M.K.; Rehman, H.; Ishtiaq, M.; Cancan, M. On analysis of temperature based topological indices of some COVID-19 drugs. Polycycl. Aromat. Compd. 2023, 43, 3810–3826. [Google Scholar] [CrossRef]
Temperature Index Name | Definition |
---|---|
(a, b)-temperature index [19] | |
Sum connectivity temperature index [19] | |
Product connectivity temperature index [19] | |
Symmetric division temperature index [19] | |
Temperature Sombor index [20] |
Number of Edges | |
---|---|
3 | |
1 | |
3 | |
3 | |
1 |
Number of Edges | |
---|---|
3 | |
11 | |
18 | |
6 |
Number of Edges | |
---|---|
1 | |
2 | |
6 | |
9 | |
2 |
Number of Edges | |
---|---|
1 | |
2 | |
6 | |
12 | |
5 |
Number of Edges | |
---|---|
2 | |
1 | |
2 | |
4 | |
4 |
Drugs | BP | EN | FP | MR | MV | PO |
---|---|---|---|---|---|---|
Carmustine | 309.60 | 63.80 | 141.00 | 46.60 | 146.40 | 18.50 |
Convolutamine F | 728.20 | 110.10 | 394.20 | 136.60 | 367.30 | 54.10 |
Raloxifene | 391.70 | 64.10 | 190.70 | 76.60 | 235.10 | 30.40 |
Tambjamine K | 521.60 | 79.50 | 269.20 | 87.40 | 228.30 | 34.70 |
Pterocellin B | 387.70 | 63.70 | 188.30 | 73.80 | 220.10 | 29.20 |
Drugs | PT (G) | ST (G) | SDT (G) | TSO (G) |
---|---|---|---|---|
Carmustine | 57.61211 | 17.17352836 | 26.7030303 | 3.490705977 |
Convolutamine F | 78.12000 | 21.92083073 | 29.68864469 | 3.449213296 |
Raloxifene | 524.84617 | 98.26893994 | 84.01600684 | 4.171286646 |
Tambjamine K | 154.23000 | 38.38737911 | 45.9232707 | 4.041993485 |
Pterocellin B | 236.15000 | 55.60580345 | 58.24280068 | 4.212925884 |
Drugs | BP | EN | FP | MR | MV | PO |
---|---|---|---|---|---|---|
PT (G) | 0.983 | 0.983 | 0.983 | 0.966 | 0.941 | 0.967 |
ST (G) | 0.984 | 0.971 | 0.984 | 0.966 | 0.936 | 0.967 |
SDT (G) | 0.959 | 0.938 | 0.959 | 0.974 | 0.969 | 0.975 |
TSO (G) | 0.671 | 0.578 | 0.670 | 0.618 | 0.548 | 0.621 |
Physical Properties | N | A | b | R | R2 | SE | F | P | Indicator |
---|---|---|---|---|---|---|---|---|---|
BP | 5 | 288.656 | 0.852 | 0.983 | 0.966 | 35.2010 | 84.108 | 0.003 | significant |
EN | 5 | 54.315 | 0.104 | 0.983 | 0.966 | 4.27066 | 85.632 | 0.003 | significant |
FP | 5 | 128.361 | 0.515 | 0.983 | 0.966 | 21.2897 | 84.102 | 0.003 | significant |
MR | 5 | 48.899 | 0.168 | 0.966 | 0.934 | 9.78020 | 42.328 | 0.007 | significant |
MV | 5 | 156.065 | 0.397 | 0.941 | 0.885 | 31.29009 | 23.067 | 0.017 | significant |
PO | 5 | 19.405 | 0.066 | 0.967 | 0.935 | 3.84476 | 42.922 | 0.007 | significant |
Physical Properties | N | A | b | R | R2 | SE | F | P | Indicator |
---|---|---|---|---|---|---|---|---|---|
BP | 5 | 240.117 | 4.948 | 0.984 | 0.968 | 33.7133 | 91.966 | 0.002 | significant |
EN | 5 | 48.764 | 0.597 | 0.971 | 0.942 | 5.59077 | 48.717 | 0.006 | significant |
FP | 5 | 99.006 | 2.992 | 0.984 | 0.968 | 20.3959 | 91.904 | 0.002 | significant |
MR | 5 | 39.399 | 0.974 | 0.966 | 0.934 | 9.78322 | 42.299 | 0.007 | significant |
MV | 5 | 134.146 | 2.289 | 0.936 | 0.876 | 32.4480 | 21.240 | 0.01 | significant |
PO | 5 | 15.641 | 0.386 | 0.967 | 0.935 | 3.83327 | 43.198 | 0.007 | significant |
Physical Properties | N | A | b | R | R2 | SE | F | P | Indicator |
---|---|---|---|---|---|---|---|---|---|
BP | 5 | 166.496 | 6.624 | 0.959 | 0.920 | 53.7884 | 34.307 | 0.01 | significant |
EN | 5 | 40.170 | 0.793 | 0.938 | 0.880 | 8.03429 | 22.043 | 0.018 | significant |
FP | 5 | 54.473 | 4.007 | 0.959 | 0.920 | 32.5155 | 34.341 | 0.01 | significant |
MR | 5 | 22.859 | 1.349 | 0.974 | 0.949 | 8.5775 | 55.929 | 0.005 | significant |
MV | 5 | 91.371 | 3.256 | 0.969 | 0.939 | 22.6902 | 46.571 | 0.006 | significant |
PO | 5 | 9.097 | 0.534 | 0.975 | 0.939 | 3.3647 | 56.957 | 0.005 | significant |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Shi, X.; Cai, R.; Ramezani Tousi, J.; Talebi, A.A. Quantitative Structure–Property Relationship Analysis in Molecular Graphs of Some Anticancer Drugs with Temperature Indices Approach. Mathematics 2024, 12, 1953. https://doi.org/10.3390/math12131953
Shi X, Cai R, Ramezani Tousi J, Talebi AA. Quantitative Structure–Property Relationship Analysis in Molecular Graphs of Some Anticancer Drugs with Temperature Indices Approach. Mathematics. 2024; 12(13):1953. https://doi.org/10.3390/math12131953
Chicago/Turabian StyleShi, Xiaolong, Ruiqi Cai, Jaber Ramezani Tousi, and Ali Asghar Talebi. 2024. "Quantitative Structure–Property Relationship Analysis in Molecular Graphs of Some Anticancer Drugs with Temperature Indices Approach" Mathematics 12, no. 13: 1953. https://doi.org/10.3390/math12131953
APA StyleShi, X., Cai, R., Ramezani Tousi, J., & Talebi, A. A. (2024). Quantitative Structure–Property Relationship Analysis in Molecular Graphs of Some Anticancer Drugs with Temperature Indices Approach. Mathematics, 12(13), 1953. https://doi.org/10.3390/math12131953