In silico Screening and in vitro Cytotoxicity Study of Achyranthes aspera Phytochemicals Against Oral Cancer: A Possible Step towards the Development of Anti-cancer Agents.

IF 1.6 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS Combinatorial chemistry & high throughput screening Pub Date : 2024-07-11 DOI:10.2174/0113862073289916240503051643

Juveriya Israr, Mohsin Ali Khan, Sankalp Misra, Divya Gupta, Nootan Singh, Rumana Ahmad, Sahabjada Siddiqui

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Abstract

Background: Oral cancer poses a significant threat to public health worldwide. In addition, because many chemotherapy treatments have negative side effects, natural herbs may be beneficial for oral cancer therapy. Achyranthes aspera (AA), a potential medicinal herb, exerts various pharmacological and biochemical activities.

Objective: The present study aimed to predict the anti-oral cancer potential of AA using in silico tools and cell death by in vitro testing.

Methods: A total of fourteen bioactive constituents from AA herb were selected using phytochemical databases. The toxicity of AA herb extract was analysed through MTT assay against oral carcinoma A253 cell line. The binding activities of the phytocomponents against serine/ threonine-specific protein kinases isoforms, namely Akt1 (PDB ID: 3qkk) and Akt2 (PDB ID: 2jdo) proteins, were analysed using Discovery Studio 2021 and PyRx docking software.

Results: Cell viability data revealed that AA extract decreased the viability and reduced the number of live cells of the oral carcinoma A253 cell line in a dose-dependent manner. The halfmaximal concentration (IC50) value of AA was assessed as 204.74 μg/ml. Based on binding affinity, saponin C (-CDOCKER energy = -77.9862), oleanolic acid (-CDOCKER energy = - 49.4349), spinasterol (-CDOCKER energy = -38.1246), 36,47-dihydroxyhenpentacontan-4-one (-CDOCKER energy = -32.4386), and 20-hydroxyecdysone (-CDOCKER energy = -31.9138) were identified as the best compounds against Akt1, while, compounds saponin C (-CDOCKER energy = -134.412), oleanolic acid (-CDOCKER energy = -90.0846), spinasterol (-CDOCKER energy = -78.3213), 20-hydroxyecdysone (-CDOCKER energy = -80.1049), and ecdysone (- CDOCKER energy = -73.3885) were identified as Akt2 inhibitors. These top compounds fulfilled drug score values, pharmacokinetic and physicochemical characteristics, and druglikeness parameters.

Conclusion: The present findings reveal that the lead phytomolecules of AA could be effective and developed as a prospective drug against oral cancer.

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欧当归植物化学物质对口腔癌的硅学筛选和体外细胞毒性研究：开发抗癌药物的可能步骤。

背景：口腔癌对全球公众健康构成重大威胁。此外，由于许多化疗方法都有负面影响，天然草药可能对口腔癌治疗有益。牛膝（AA）是一种潜在的药用植物，具有多种药理和生化活性：本研究旨在利用硅学工具预测 AA 的抗口腔癌潜力，并通过体外测试预测细胞死亡情况：方法：利用植物化学数据库从 AA 草药中筛选出 14 种生物活性成分。通过 MTT 试验分析了 AA 草本提取物对口腔癌 A253 细胞株的毒性。使用 Discovery Studio 2021 和 PyRx docking 软件分析了植物成分与丝氨酸/苏氨酸特异性蛋白激酶同工酶（即 Akt1（PDB ID：3qkk）和 Akt2（PDB ID：2jdo）蛋白）的结合活性：细胞活力数据显示，AA 提取物以剂量依赖的方式降低了口腔癌 A253 细胞系的活力并减少了活细胞数量。经评估，AA 的半最大浓度（IC50）为 204.74 μg/ml。根据结合亲和力，皂苷 C（-CDOCKER 能量 = -77.9862）、齐墩果酸（-CDOCKER 能量 = -49.4349）、刺五加醇（-CDOCKER 能量 = -38.1246）、36,47-二羟基苯并五碳-4-酮（-CDOCKER 能量 = -32.4386）和 20-羟基蜕皮激素（-CDOCKER 能量 = -31.9138）被鉴定为抑制 Akt1 的最佳化合物，而皂苷 C（-CDOCKER 能量 = -134.412）、齐墩果酸（-CDOCKER 能量 = -90.0846）、刺五加醇（-CDOCKER 能量 = -78.3213）、20-羟基蜕皮激素（-CDOCKER 能量 = -80.1049）和蜕皮激素（-CDOCKER 能量 = -73.3885）被鉴定为 Akt2 抑制剂。这些顶级化合物符合药物评分值、药动学和理化特征以及药物亲和性参数：本研究结果表明，AA 的主要植物大分子可作为一种有效的抗口腔癌药物进行开发。

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来源期刊

Combinatorial chemistry & high throughput screening 化学-生化研究方法

CiteScore

3.10

自引率

5.60%

发文量

327

审稿时长

7.5 months

期刊介绍： Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.