Author ORCID Identifier
0009-0006-3029-7825
Biosketch
A. Gayathri has qualified for the degree of Doctor of Philosophy (Ph.D.) from the Department of Mathematics, SrinivasaRamanujan Centre, SASTRA Deemed University, Kumbakonam, Tamil Nadu, India. Her doctoral research focuses on Chemical Graph Theory, with particular emphasis on the development of novel Open-Neighbourhood-Edge-Degree (ONE) indices and their applications in Quantitative Structure–Property Relationship (QSPR) modelling, metric descriptors, and Multi-Criteria Decision Making (MCDM) for the analysis of chemical compounds and influenza antiviral drugs.
Her research has resulted in publications in SCIE and Scopus-indexed journals. She has contributed to the advancement of mathematical chemistry by introducing new graph-theoretical descriptors and demonstrating their effectiveness in molecular property prediction, computational analysis of benzenoid structures, and the ranking of antiviral drugs. Her research interests include Chemical Graph Theory, Topological Indices, QSPR Modelling, Mathematical Chemistry, Graph Algorithms, and Decision-Making Techniques.
She is committed to interdisciplinary research that integrates mathematics, chemistry, and computational methods to develop innovative approaches for molecular modelling, cheminformatics, and drug discovery.
Date of Award
6-7-2026
Document Type
Thesis
School
School of Arts, Sciences, Humanities & Education
Programme
Ph.D.-Doctoral of Philosophy
First Advisor
Dr.D.Narasimhan
Keywords
Chemical Graph theory, Open-Neighbourhood-Edge-Degree Indices, Topological Indices
Abstract
Chemical Graph theory offers powerful computational methods for evaluating chemical structures, significantly impacting cheminformatics and drug analysis. It provides a robust mathematical framework to represent, model, and analyse molecular systems through topological indices and graph invariants. These indices serve as effective numerical descriptors, encapsulating significant structural information that enhances the prediction of physicochemical and biological properties. This thesis utilizes mathematical modeling, algorithmic computation, and decision making process to derive extensive insights to drug discovery and molecular analysis.
The thesis introduces a new class of topological indices ONE1, ONE2, ONE3, ONE4, ONE5,ONE6 and ONE7 based on open-neighbourhood-edge-degree and it evaluates the discriminating abilities of these indices through mean isomer degeneracy and sensitivity analysis for structural isomers of nonane and decane. Linear QSPR analysis reveals strong correlations between the physicochemical properties including the acentric factor, logP, and delta fusion, for the nonane and decane isomers and the proposed indices.
Also, the proposed indices are applied for complex molecular structures, the openneighbourhood- edge-degree based indices were computed for the circumcoronene series of benzenoid structure, and they were numerically and graphically analysed using MATLAB. Further an algorithm is developed for computing the proposed indices for general graphs. Additionally, QSPR analysis was performed employing the proposed indices and the physicochemical properties of antiviral drugs for influenza. The antiviral drugs considered for the study includes - Amantadine, Rimantadine, Oseltamivir, Zanamivir, Peramivir, Laninamivir, Baloxavir Marboxil, and Favipiravir. The calculated values from QSPR analysis are applied to the VIKOR Multi-Criteria Decision Making method to rank these antiviral drugs based on multiple physicochemical properties.
Further, the metric dimension and fault-tolerant metric dimension for these antiviral drugs against influenza were computed, and QSPR analysis was performed using these descriptors and the physicochemical properties of the antiviral drugs. In addition, spectral based descriptors, including Graph energy and Laplacian energy, were also calculated for these antiviral drugs using the R programming language. Thus, this study establishes an integrated graph-theoretic framework linking topological, metric, and decision-making approaches to provide a comprehensive structural assessment of chemical compounds and antiviral drugs.
Recommended Citation
A, Gayathri Ms, "Open Neighbourhood Edge Degree and Metric Descriptors QSPR and Multi Criteria Analysis of Chemicals and Antiviral Drugs" (2026). Theses and Dissertations. 222.
https://knowledgeconnect.sastra.edu/theses/222