Utilizing neighborhood topological indices for QSPR analysis of clinically approved immunosuppressive drugs in heart transplant therapy

IF 2.6 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry Pub Date : 2025-03-11 DOI:10.1016/j.compbiolchem.2025.108414

R. Thamizhmaran , G. Kalaimurugan , Muhammad Kamran Siddiqui , L. Vinnarasi , A. Yuvaraj , Muhammad Faisal Hanif

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Abstract

Heart transplantation is a life-saving transplantation procedure for individuals with advanced heart failure who have gone through all other medicinal options. It is predicted that 5000 heart transplants will be performed annually worldwide. The immunosuppressive drugs are used after a heart transplant to prevent organ rejection. They may be administered both before and throughout the transplant process under specific circumstances. Quantitative Structure-Activity or Property Relationship using topological descriptors is essential in drug design since it allows one to anticipate the physicochemical characteristics of medications based on their molecular structure. This study investigates the neighborhood topological descriptors of immunosuppressive medications used to treat heart transplant patients. The highest predictive efficacy of the pharmaceuticals is demonstrated by the good association between the topological indicators and the physical characteristics of the transplant medications. Additionally, this data may be used by researchers to develop new and effective medications for recipients of heart transplants.

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心脏移植是一种拯救生命的移植手术，适用于已用尽所有其他药物治疗方法的晚期心力衰竭患者。据预测，全世界每年将进行 5000 例心脏移植手术。免疫抑制剂用于心脏移植后防止器官排斥反应。在特定情况下，可在移植前和整个移植过程中使用。使用拓扑描述符的定量结构-活性或性质关系在药物设计中至关重要，因为它允许人们根据药物的分子结构预测药物的理化特性。本研究调查了用于治疗心脏移植患者的免疫抑制药物的邻域拓扑描述符。拓扑指标与移植药物物理特性之间的良好关联证明了药物的最高预测效力。此外，研究人员还可利用这些数据为心脏移植受者开发新的有效药物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational Biology and Chemistry 生物-计算机：跨学科应用

CiteScore

6.10

自引率

3.20%

发文量

142

审稿时长

24 days

期刊介绍： Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.