AccScience Publishing / IJOCTA / Online First / DOI: 10.36922/IJOCTA026040011
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RESEARCH ARTICLE

Integration of topological indices and QSPR modeling with VIKOR-based multi-criteria decision analysis for evaluating eye drug candidates

Muhammad Kamran1,2,3 ,  Shereen Iqbal4 ,  Hifza Iqbal4* ,  Muhammad Akhtar Tarar5 ,  Muhammad Farman1,6 ,  Evren Hincal1,7 ,  Mohamad Hafez3,8
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1 Mathematics Research Center, Department of Mathematics Near East University, Mersin, Turkey
2 International Center for Interdisciplinary Research in Sciences, The University of Lahore, Lahore, Pakistan
3 Department of Mathematics, Faculty of Engineering and Quantity Surviving, INTI International University Colleges, Nilai, Negeri Sembilan, Malaysia
4 Department of Mathematics and Statistics, The University of Lahore, Lahore, Punjab, Pakistan
5 Department of Civil Engineering, The University of Lahore, Lahore, Punjab, Pakistan
6 Department of Computer Engineering, Biruni University, Istanbul, Turkey
7 Research Center of Applied Mathematics, Khazar University, Baku, Azerbaijan
8 Department of Management, Faculty of Management, Shinawatra University, Pathum Thani, Thailand
IJOCTA, 026040011 https://doi.org/10.36922/IJOCTA026040011
Received: 19 January 2026 | Revised: 12 March 2026 | Accepted: 19 March 2026 | Published online: 13 May 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Topological indices encode molecular structure into numerical descriptors, enabling prediction of physicochemical properties without extensive experimentation. This study evaluates the implementation of graph-theoretical topological indices in combination with multi-criteria decision-making methods to compute physicochemical properties and ranking of eye drugs. A set of classical topological indices, consisting of N SK1, N SK2, M1, M2, N M1, N M2, N SK, N F , and N H, are computed using an edge-partition approach to describe the structural aspects of 12 selected drugs. Multiple linear regression models were developed to develop quantitative structure–property relationship models for important physicochemical properties, including molar volume, polarizability, molar weight, and molar refraction. The multiple linear regression models showed reliable predictive output, with statistical indicators and correlation coefficients higher than 0.89, confirming the value of the selected indices. The VIKOR technique enables the ranking of drugs based on their estimated physicochemical properties. The combined application of quantitative structure–property relationship and multi-criteria decision-making framework enhances robustness in discriminating structurally similar eye drugs. This combination offers a systematic framework for prioritizing compounds in pharmacological research and drug optimization. Such approach also supports public health by facilitating more efficient drug development and therapeutic decision-making for eye diseases. 

Keywords
Graph theory
Multi-criteria decision-making
Multiple linear regression
Public health
Quantitative structure–property relationship ranking
VIKOR
Funding
This work is funded by Faculty of Engineering and Quantity Surviving, INTI International University Colleges, Nilai, Malaysia.
Conflict of interest
The authors declare they have no competing interests.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing
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