Yadalam Pradeep Kumar, Anegundi Raghavendra Vamsi, Ramadoss Ramya, Shrivastava Deepti, Almufarrij Raha Ahmed Shamikh, Srivastava Kumar Chandan
Department of Periodontics, Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.
Department of Oral Biology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
Technol Health Care. 2024;32(5):3007-3019. doi: 10.3233/THC-231358.
Wnt activation promotes bone formation and prevents bone loss. The Wnt pathway antagonist sclerostin and additional anti-sclerostin antibodies were discovered as a result of the development of the monoclonal antibody romosozumab. These monoclonal antibodies greatly increase the risk of cardiac arrest. Three-dimensional quantitative structure-activity relationships (3D-QSAR) predicts biological activities of ligands based on their three-dimensional features by employing powerful chemometric investigations such as artificial neural networks (ANNs) and partial least squares (PLS).
In this study, ligand-receptor interactions were investigated using 3D-QSAR Comparative molecular field analysis (CoMFA). Estimates of steric and electrostatic characteristics in CoMFA are made using Lennard-Jones and Coulomb potentials.
To identify the conditions necessary for the activity of these molecules, fifty Food and Drug Administration (FDA)-approved medications were chosen for 3D-QSAR investigations and done by CoMFA. For QSAR analysis, there are numerous tools available. This study employed Open 3D-QSAR for analysis due to its simplicity of use and capacity to produce trustworthy results. Four tools were used for the analysis on this platform: Py-MolEdit, Py-ConfSearch, and Py-CoMFA.
Maps that were generated were used to determine the screen's r2 (Coefficient of Multiple Determinations) value and q2 (correlation coefficient). These numbers must be fewer than 1, suggesting a good, trustworthy model. Cross-validated (q2) 0.532 and conventional (r2) correlation values of 0.969 made the CoMFA model statistically significant. The model showed that hydroxamic acid inhibitors are significantly more sensitive to the steric field than the electrostatic field (70%) (30%). This hypothesis states that steric (43.1%), electrostatic (26.4%), and hydrophobic (20.3%) qualities were important in the design of sclerostin inhibitors.
With 3D-QSAR and CoMFA, statistically meaningful models were constructed to predict ligand inhibitory effects. The test set demonstrated the model's robustness. This research may aid in the development of more effective sclerostin inhibitors that are synthesised using FDA-approved medications.
Wnt激活可促进骨形成并预防骨质流失。Wnt通路拮抗剂硬化蛋白以及其他抗硬化蛋白抗体是在单克隆抗体罗莫单抗的研发过程中被发现的。这些单克隆抗体极大地增加了心脏骤停的风险。三维定量构效关系（3D-QSAR）通过运用强大的化学计量学研究方法，如人工神经网络（ANNs）和偏最小二乘法（PLS），基于配体的三维特征预测其生物活性。
在本研究中，使用3D-QSAR比较分子场分析（CoMFA）研究配体-受体相互作用。CoMFA中的空间和静电特征估计是使用 Lennard-Jones和库仑势进行的。
为确定这些分子活性所需的条件，选择了五十种美国食品药品监督管理局（FDA）批准的药物进行3D-QSAR研究，并通过CoMFA完成。对于QSAR分析，有许多可用工具。本研究采用Open 3D-QSAR进行分析，因其使用简单且能够产生可靠结果。在该平台上使用了四种工具进行分析：Py-MolEdit、Py-ConfSearch和Py-CoMFA。
生成的图谱用于确定筛选的r2（多重决定系数）值和q2（相关系数）。这些数值必须小于1，表明是一个良好、可靠的模型。交叉验证（q2）为0.532，传统（r2）相关值为0.969，使得CoMFA模型具有统计学意义。该模型表明，异羟肟酸抑制剂对空间场的敏感性明显高于静电场（70%）（30%）。该假设指出，空间（43.1%）、静电（26.4%）和疏水（20.3%）性质在硬化蛋白抑制剂的设计中很重要。
通过3D-QSAR和CoMFA构建了具有统计学意义的模型来预测配体抑制作用。测试集证明了该模型的稳健性。本研究可能有助于开发使用FDA批准药物合成的更有效的硬化蛋白抑制剂。
