IJCOPE Journal

UGC Logo DOI / ISO Logo

International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
Journal Information
ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 7

Published on: July 2026

TOPOLOGICAL ANALYSIS OF HIV/AIDS DRUGS USING GRAPH THEORY, LINEAR REGRESSION MODELS, AND PREDICTIVE MACHINE LEARNING SUITES

R Kiran Kumar K Abhishek

Jyothy Institute of Technology, Pipeline Rd,

Near Ravi Shankar Guruji Ashram, Tatguni, Bengaluru, Agara, Karnataka 560082, India

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

This research article integrates molecular graph theory with computational data science techniques to analyze the physicochemical behavior of drugs used against HIV/AIDS disease. Quantitative Structure-Property Relationship (QSPR) models are built using topological descriptors specifically the 4th Degree-Sum Product (4-DSP) index and the Logarithmic Fraction Degree Square Sum (LFDS) index for four drugs. We bridge standard graph theoretical derivations with advanced multi-model machine learning techniques. Evaluations are conducted via strict localized training fits alongside Leave-One-Out Cross-Validation (LOOCV) loops to gauge predictive stability over sparse molecular sample frameworks.


KEYWORDS:
QSPR analysis, Linear Regression, XGBoost, Support Vector Regression, 4-DSP index, LFDS index.

How to Cite this Paper

Kumar, R. K. & Abhishek, K. (2026). Topological Analysis of HIV/AIDS Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(7), 1-9. https://doi.org/10.55041/ijcope.v2i7.166

Kumar, R, and K Abhishek. "Topological Analysis of HIV/AIDS Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i7.166.

Kumar, R, and K Abhishek. "Topological Analysis of HIV/AIDS Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i7.166.

Search & Index

References


  • Ahmed, W., Zaman, S., Asif, E., Ali, K., Mahmoud, E. E., & Asheboss, M. A. (2024). Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms. BMC Chemistry, 18, 167.

  • Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5-32.

  • Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 785-794).

  • Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273-297.

  • Drucker, H., Burges, C. J., Kaufman, L., Smola, A., & Vapnik, V. (1996). Support vector regression machines. Advances in Neural Information Processing Systems, 9, 155-161.

  • Farooq, A., et al. (2023). Multi-criteria decision-making optimization models for complex structural HIV drugs. Journal of Mathematical Chemistry, 61(4), 789-804.

  • Harary, F. (1969). Graph Theory. Addison-Wesley, Reading, MA.

  • Havare, Ö. Ç. (2021). Topological indices and QSPR modeling of some novel drugs used in the cancer treatment. International Journal of Quantum Chemistry, 121(24), e26813.

  • Kirmani, S. A. K., Ali, P., & Azam, F. (2021). Topological indices and QSPR/QSAR analysis of some antiviral drugs being investigated for the treatment of COVID-19 patients. International Journal of Quantum Chemistry, 121(9), e26594.

  • Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to Linear Regression Analysis. John Wiley & Sons.

Ethical Compliance & Review Process

  • All submissions are screened under plagiarism detection.
  • Review follows editorial policy.
  • Authors retain copyright.
  • Peer Review Type: Double-Blind Peer Review
  • Published on: Jul 15 2026
CCBYNC

This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

View License
Scroll to Top