Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms

Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms

Abstract In order to explore the role of topological indices for predicting physio-chemical properties of anti-HIV drugs, this research uses python program-based algorithms to compute topological indices as well as machine learning algorithms. Degree-based topological indices are calculated using Py...

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Bibliographic Details
Main Authors: Wakeel Ahmed, Shahid Zaman, Eizzah Asif, Kashif Ali, Emad E. Mahmoud, Mamo Abebe Asheboss
Format: Article
Language:English
Published: BMC 2024-09-01
Series:BMC Chemistry
Subjects:
Anti-HIV-1 drugs
Topological indices
Python algorithm
Machine learning algorithm
QSPR analysis
Online Access:https://doi.org/10.1186/s13065-024-01266-4

Internet

https://doi.org/10.1186/s13065-024-01266-4

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