3D and 2D-QSAR Studies on Natural Flavonoids for Nitric Oxide Production Inhibitory Activity

IF 1.2 4区医学 Q4 CHEMISTRY, MEDICINAL

Letters in Drug Design & Discovery Pub Date : 2024-01-11 DOI:10.2174/0115701808179188231205064327

Chunqiang Wang, Yuzhu Fan, Minfan Pei, Chaoqun Yan, Taigang Liang

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引用次数: 0

Abstract

Background: Nitric oxide (NO), an important second messenger molecule, regulates numerous physiological responses, while excessive NO generates negative effects on the circulatory, nervous and immune systems. Recently, some natural flavonoids were reported to possess the capability of inhibiting LPS-induced NO production. To fully understand the nature of their own NO inhibitory activity, it is necessary to address the structural requirements of flavonoids as NO inhibitors. Objective: The objective of this work was to develop efficient QSAR models for predicting the NOinhibitory activity of new flavonoids and improving insights into the critical properties of the chemical structures that were required for the ideal NO production inhibitory activities. Methods: To provide insights into the structural basis of flavonoids as NO inhibitors, 3D quantitative structure-activity relationship (3D-QSAR) and 2D-QSAR models were developed on a dataset of 55 flavonoids using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) approaches. method: CoMFA, CoMSIA combining HQSAR methods were employed on a series of flavonoids to generate 3D and 2D-QSAR models. Results: The statistically significant models for CoMFA, CoMSIA and HQSAR resulted in crossvalidated coefficient (q2) values of 0.523, 0.572 and 0.639, non-cross-validated coefficient (r2) values of 0.793, 0.828 and 0.852, respectively. The robustness of these models was further affirmed using a test set of 18 compounds, which resulted in predictive correlation coefficients (r2 pred) of 0.968, 0.954 and 0.906. Furthermore, the models-derived contour maps were appraised for activity trends for the molecules analyzed. result: Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA) combining hologram quantitative structure-activity relationship (HQSAR) methods were employed on a series of flavonoids to generate 3D and 2D-QSAR models. Result: The obtained models can be used to predict the activities of new flavonoids and identify the key structural features affecting the NO inhibitory activities. Conclusion: The 3D and 2D-QSAR models constructed in this paper were efficient in estimating the NO inhibitory activities of flavonoids and facilitating the design of flavonoid-derived NO production inhibitors. other: none

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天然类黄酮抑制一氧化氮生成活性的三维和二维 QSAR 研究

背景：一氧化氮（NO）是一种重要的第二信使分子，可调节多种生理反应，而过量的一氧化氮会对循环系统、神经系统和免疫系统产生负面影响。最近有报道称，一些天然类黄酮具有抑制 LPS 诱导的一氧化氮产生的能力。为了充分了解其自身 NO 抑制活性的性质，有必要解决黄酮类化合物作为 NO 抑制剂的结构要求。目标：这项工作的目的是建立有效的 QSAR 模型，以预测新黄酮类化合物的 NO 抑制活性，并深入了解理想的 NO 生成抑制活性所需的化学结构的关键特性。方法：为了深入了解黄酮类化合物作为氮氧化物抑制剂的结构基础，采用比较分子场分析（CoMFA）、比较分子相似性指数分析（CoMSIA）和全息图定量结构-活性关系（HQSAR）方法，在55种黄酮类化合物的数据集上建立了三维定量结构-活性关系（3D-QSAR）和二维QSAR模型：对一系列黄酮类化合物采用 CoMFA、CoMSIA 和 HQSAR 方法生成三维和二维 QSAR 模型。结果：CoMFA、CoMSIA 和 HQSAR 的统计意义模型的交叉验证系数 (q2) 值分别为 0.523、0.572 和 0.639，非交叉验证系数 (r2) 值分别为 0.793、0.828 和 0.852。使用 18 种化合物的测试集进一步证实了这些模型的稳健性，其预测相关系数（r2 pred）分别为 0.968、0.954 和 0.906。此外，还对模型得出的等高线图进行了评估，以确定所分析分子的活性趋势：对一系列黄酮类化合物采用比较分子场分析法（CoMFA）、比较分子相似性指数分析法（CoMSIA）和全息图定量结构-活性关系法（HQSAR）生成三维和二维 QSAR 模型。结果：获得的模型可用于预测新黄酮类化合物的活性，并确定影响 NO 抑制活性的关键结构特征。结论本文构建的三维和二维 QSAR 模型可有效地估算类黄酮的 NO 抑制活性，并有助于设计类黄酮衍生的 NO 生成抑制剂。其他：无

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来源期刊

Letters in Drug Design & Discovery 医学-医药化学

CiteScore

1.80

自引率

10.00%

发文量

245

审稿时长

3 months

期刊介绍： Aims & Scope Letters in Drug Design & Discovery publishes letters, mini-reviews, highlights and guest edited thematic issues in all areas of rational drug design and discovery including medicinal chemistry, in-silico drug design, combinatorial chemistry, high-throughput screening, drug targets, and structure-activity relationships. The emphasis is on publishing quality papers very rapidly by taking full advantage of latest Internet technology for both submission and review of manuscripts. The online journal is an essential reading to all pharmaceutical scientists involved in research in drug design and discovery.