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ORIGINAL RESEARCH article
Front. Chem.
Sec. Theoretical and Computational Chemistry
Volume 12 - 2024 |
doi: 10.3389/fchem.2024.1486933
New Reverse Sum Revan Indices for Physicochemical and Pharmacokinetic Properties of Anti-filovirus Drugs
Provisionally accepted- Vellore Institute of Technology (VIT), Chennai, India
Ebola and Marburg viruses, biosafety level 4 pathogens, cause severe hemorrhaging and organ failure with high mortality. Although some FDA-approved vaccines or therapeutics like Ervebo for Zaire Ebola virus exist, still there is a lack of effective therapeutics that cover all filoviruses, including both Ebola and Marburg viruses. Therefore, some anti-filovirus drugs such as Pinocembrin, Favipiravir, Remdesivir and others are used to manage infections. In theoretical chemistry, a chemical molecule is converted into an isomorphic molecular graph, 𝐺(𝑉, 𝐸) by considering atom set 𝑉 as vertices and bond set 𝐸 as edges. A topological index is a molecular descriptor derived from the molecular graph of a chemical compound that characterizes its topology. The relationship between a compound's chemical structure and its properties is investigated through the quantitative structure-property relationship (QSPR). This article introduces new reverse sum Revan degree based indices to explore the physicochemical and pharmacokinetic properties of anti-filovirus drugs via multilinear regression. The findings reveal a strong correlation between these proposed indices and the properties of anti-filovirus drugs when compared to reverse and Revan degree-based indices. Thus, reverse sum Revan indices offer valuable insights for analyzing the drugs properties used to treat Ebola and Marburg virus infections. Moreover, the multilinear regression (MLR) results through reverse sum Revan indices are compared with Artificial Neural Network (ANN) modelling technique and it provides the better prediction of the physicochemical and pharmacokinetic properties of anti-filovirus drugs.
Keywords: Anti-filovirus drugs, Ebola virus, Marburg virus, Reverse sum Revan index, QSPR, Multilinear regression, artificial neural network
Received: 27 Aug 2024; Accepted: 21 Nov 2024.
Copyright: © 2024 W and Bommahalli Jayaraman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Balamurugan Bommahalli Jayaraman, Vellore Institute of Technology (VIT), Chennai, India
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