Metric analysis of molecular graphs of selected anticancer drugs

Aims This study aims to analyze the molecular structures of anticancer drugs using graph-theoretic parameters and to investigate their structural properties through metric-based descriptors.Materials and methods The chemical structures of vorinostat and tucidinostat are modeled as molecular graphs. Graph theoretical concepts such as metric dimension (MD), edge metric dimension (EMD), and fault-tolerant metric dimension (FTMD) are applied to study these drug molecules.Results The computed invariants provide quantitative information about structural uniqueness, bond distinguishability, and robustness of the molecular graphs. The results show differences in structural complexity and stability between the two drugs based on MD, EMD, and FTMD values.Conclusions The study demonstrates that these graph-theoretic parameters effectively capture important structural features of anticancer drugs. They may be useful in mathematical chemistry, molecular modeling, and drug structure analysis for future research.

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Publication Details

Journal
Future Medicinal Chemistry
Published
2026-06-13
DOI
https://doi.org/10.1080/17568919.2026.2688858
Primary Topic
Graph Labeling and Dimension Problems
Type
article
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article

Metric analysis of molecular graphs of selected anticancer drugs

Vijay Kumar Bhat, Sandeep Kumar
Future Medicinal Chemistry
Graph Labeling and Dimension Problems
article

Metric analysis of molecular graphs of selected anticancer drugs

Vijay Kumar Bhat, Sandeep Kumar
article en

Abstract

Aims This study aims to analyze the molecular structures of anticancer drugs using graph-theoretic parameters and to investigate their structural properties through metric-based descriptors.Materials and methods The chemical structures of vorinostat and tucidinostat are modeled as molecular graphs. Graph theoretical concepts such as metric dimension (MD), edge metric dimension (EMD), and fault-tolerant metric dimension (FTMD) are applied to study these drug molecules.Results The computed invariants provide quantitative information about structural uniqueness, bond distinguishability, and robustness of the molecular graphs. The results show differences in structural complexity and stability between the two drugs based on MD, EMD, and FTMD values.Conclusions The study demonstrates that these graph-theoretic parameters effectively capture important structural features of anticancer drugs. They may be useful in mathematical chemistry, molecular modeling, and drug structure analysis for future research.

Future Medicinal Chemistry
Shri Mata Vaishno Devi University (IN)
Openalex Percentile: Top 4%
Graph Labeling and Dimension Problems
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Metric analysis of molecular graphs of selected anticancer drugs — Vijay Kumar Bhat, Sandeep Kumar · Future Medicinal Chemistry (2026) | TGRS Research Map | TGRS