QSPR analysis of the drugs used to treat renal failure and its complications using degree and modified reverse degree indices

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Authors: J. J. Jeni Godlin, S. Radha
Cited by: 3
References: 53

Abstract

QSPR plays a crucial role in drug design by predicting the biological activity and the physico-chemical properties of compounds based on their molecular structures. The indices based on topology are important in QSPR analysis that serve as numerical descriptors that capture structural features of molecules, enabling accurate property prediction without extensive experimental work. Renal failure and its complications are marked by progressive loss of kidney function and systemic effects, often leading to complex management challenges and increased morbidity and mortality. This research study concentrates on the structural characteristics of medications used for treating renal failure and its complications, including sotagliflozin, vadadustat, empagliflozin, canagliflozin, daprodustat, calcitriol, pravastatin, pitavastatin, paricalcitol, dapagliflozin, finerenone, cinacalcet, irbesartan, captopril, doxercalciferol, epoetin alfa, hydrochlorothiazide, tenapanor, and etelcalcetide. We have done QSPR analysis incorporating degree and modified reverse degree indices and performed a comparison to demonstrate our models’ efficacy.

Fields of Study & Subjects

Computational Drug Discovery Methods Graph theory and applications Machine Learning in Bioinformatics

Publication details

Journal / source
Scientific Reports
Publisher
Springer Science and Business Media LLC
Volume
16
Issue
1
Publication date
17 February 2026
Language
EN