Mitku Melese Legesse, Dagnaw Abera Dessie, Geremew Derso Teju, Anagaw Yeniewa Kerie, Worku Minichil Chanie, Limenh Liknaw Workie, Tadesse Yabibal Berie, Ergena Asrat Elias
Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Department of Pharmaceutics, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
SAGE Open Med. 2024 Oct 16;12:20503121241274212. doi: 10.1177/20503121241274212. eCollection 2024.
In silico predictions are now being utilized in drug discovery and design to assess the physicochemical, pharmacokinetics, and safety properties of compounds at the beginning of the drug discovery process. This early evaluation of the physicochemical, pharmacokinetics, and safety properties of compounds helps the researchers to invest their time and resources only in the best prospective lead compounds by eliminating compounds with a low chance of success.
The purpose of this study was to explore a promising lead compound designed from 1-piperazine indole hybrid with nicotinic amide and nicotinic acid analogs targeted on phosphofructokinase for Trypanosomiasis activity by using in silico predictions strategy.
The physicochemical, safety, pharmacokinetic, and biological activity properties of those molecules were predicted by using ADMETlab 2.0, ACD labs Chem Sketch software version 14.0, Molinspiration software, and MolPredictX online tool. Our results indicate that several promising candidates exhibit favorable characteristics. Based on Molinspiration software both nicotinic acid and nicotinic amide derivatives showed higher kinase inhibitor activity and all nicotinic acid derivatives revealed enzyme inhibitors and GPCR ligand activity. According to the MolPredictX online tool, the most biologically active derivatives were NA-4, NA-11, and NAD-11.
Overall, our findings offer valuable insights into the potential efficacy and safety of these compounds. It appears that almost all of the compounds have successfully passed the pharmacokinetic evaluations and integration of nicotinic acid into indole appears to be more beneficial than nicotinic amide regarding certain biological activities.
在药物发现和设计过程中,计算机模拟预测正被用于评估化合物的物理化学性质、药代动力学和安全性,这一过程始于药物发现的初期。对化合物的物理化学性质、药代动力学和安全性进行早期评估,有助于研究人员通过排除成功可能性较低的化合物,将时间和资源仅投入到最有前景的先导化合物上。
本研究的目的是通过计算机模拟预测策略,探索一种由1-哌嗪吲哚与烟酰胺和烟酸类似物设计的有前景的先导化合物,该化合物靶向磷酸果糖激酶用于治疗锥虫病。
使用ADMETlab 2.0、ACD labs Chem Sketch软件版本14.0、Molinspiration软件和MolPredictX在线工具预测了这些分子的物理化学性质、安全性、药代动力学和生物活性。我们的结果表明,有几种有前景的候选物具有良好的特性。基于Molinspiration软件,烟酸和烟酰胺衍生物均显示出较高的激酶抑制活性,所有烟酸衍生物均显示出酶抑制和GPCR配体活性。根据MolPredictX在线工具,生物活性最高的衍生物是NA-4、NA-11和NAD-11。
总体而言,我们的研究结果为这些化合物的潜在疗效和安全性提供了有价值的见解。几乎所有化合物似乎都成功通过了药代动力学评估,并且在某些生物活性方面,将烟酸整合到吲哚中似乎比烟酰胺更有益。