Prediction of Pharmacokinetics of Valeric Acid: Alternative Tool to Minimize Animal Studies.

IF 2.1 4区 医学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Bindu Kumari, Dhananjay Kumar Singh, Ravi Bhushan Singh, Gireesh Kumar Singh
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引用次数: 0

Abstract

Background: The use of computer-aided toxicity and Pharmacokinetic (PK) prediction studies are of significant interest to pharmaceutical industries as a complementary approach to traditional experimental methods in predicting potential drug candidates.

Methods: In the present study, in-silico pharmacokinetic properties (ADME), drug-likeness, and toxicity profiles of valeric acid were examined using SwissADME and ADMETlab web tools.

Results: The drug-likeness prediction results revealed that valeric acid adheres to the Lipinski rule, Pfizer rule, and GlaxoSmithKline (GSK) rule. From a pharmacokinetic perspective, valeric acid is anticipated to have the best absorption profile including cell permeability and bioavailability. Plasma Protein Binding (PPB) and Blood-Brain Barrier (BBB) permeability may have a positive effect on Central Nervous System modulating (CNS). There is a minimal chance of it being a substrate for cytochrome P2D6 (CYP). Except for a "very slight risk" for eye corrosion and eye irritation, none of the well-known toxicities in valeric acid were anticipated, which was compatible with wet-lab data. The molecule possesses no environmental hazard as analyzed with common indicators such as bio-concentration factor and LC50 for fathead minnow and daphnia magna. The toxicity parameters identified valeric acid as nontoxic to androgen receptors, antioxidant response element, mitochondrial membrane receptor, heat shock element, and tumor suppressor protein (p53), except Peroxisome Proliferator-Activated Receptor- gamma (PPAR-γ) was found to be medium toxicity. However, no toxicophores were found out of seven parameters.

Conclusion: Overall, the ADMETLab evaluated that valeric acid has favorable pharmacokinetic and drug-likeness profiles, making it a promising drug candidate for new drug development.

戊酸药代动力学预测:减少动物实验的替代工具。
背景:使用计算机辅助毒性和药代动力学(PK)预测研究作为传统实验方法预测潜在候选药物的补充方法,对制药行业具有重要意义。方法:采用SwissADME和ADMETlab网络工具,对戊酸的计算机药代动力学特性(ADME)、药物相似性和毒性进行了检测。结果:药物相似性预测结果显示,戊酸符合利平斯基规则、辉瑞规则和葛兰素史克规则。从药代动力学的角度来看,戊酸预计具有最佳的吸收特征,包括细胞渗透性和生物利用度。血浆蛋白结合(PPB)和血脑屏障(BBB)通透性可能对中枢神经系统调节(CNS)有积极作用。它是细胞色素P2D6 (CYP)的底物的可能性很小。除了对眼睛腐蚀和眼睛刺激有“非常轻微的风险”外,没有预料到戊酸中已知的毒性,这与湿实验室的数据是一致的。用生物浓度因子、大水蚤LC50等常用指标分析该分子对环境无危害。毒性参数表明,戊酸对雄激素受体、抗氧化反应元件、线粒体膜受体、热休克元件和肿瘤抑制蛋白(p53)无毒,但过氧化物酶体增殖物激活受体-γ (PPAR-γ)具有中等毒性。但7个参数均未发现毒菌。结论:总体而言,ADMETLab评估戊酸具有良好的药代动力学和药物相似性特征,使其成为新药开发的有希望的候选药物。
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来源期刊
Current drug metabolism
Current drug metabolism 医学-生化与分子生物学
CiteScore
4.30
自引率
4.30%
发文量
81
审稿时长
4-8 weeks
期刊介绍: Current Drug Metabolism aims to cover all the latest and outstanding developments in drug metabolism, pharmacokinetics, and drug disposition. The journal serves as an international forum for the publication of full-length/mini review, research articles and guest edited issues in drug metabolism. Current Drug Metabolism is an essential journal for academic, clinical, government and pharmaceutical scientists who wish to be kept informed and up-to-date with the most important developments. The journal covers the following general topic areas: pharmaceutics, pharmacokinetics, toxicology, and most importantly drug metabolism. More specifically, in vitro and in vivo drug metabolism of phase I and phase II enzymes or metabolic pathways; drug-drug interactions and enzyme kinetics; pharmacokinetics, pharmacokinetic-pharmacodynamic modeling, and toxicokinetics; interspecies differences in metabolism or pharmacokinetics, species scaling and extrapolations; drug transporters; target organ toxicity and interindividual variability in drug exposure-response; extrahepatic metabolism; bioactivation, reactive metabolites, and developments for the identification of drug metabolites. Preclinical and clinical reviews describing the drug metabolism and pharmacokinetics of marketed drugs or drug classes.
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