Abstract：
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
摘要：
■Wnt激活促进骨形成并防止骨丢失。作为单克隆抗体romosozumab的开发的结果,发现了Wnt途径拮抗剂硬化素和另外的抗硬化素抗体。这些单克隆抗体大大增加了心脏骤停的风险。三维定量结构-活性关系（3D-QSAR）通过采用强大的化学计量学研究，例如人工神经网络（ANN）和偏最小二乘（PLS），根据配体的三维特征预测配体的生物活性。
■在这项研究中，使用3D-QSAR比较分子场分析(CoMFA)研究配体-受体相互作用。CoMFA中的空间和静电特性的估计是使用Lennard-Jones和库仑电位进行的。
■为了确定这些分子活性所必需的条件，选择了50种食品和药物管理局（FDA）批准的药物进行3D-QSAR研究，并由CoMFA完成。对于QSAR分析，有许多可用的工具。这项研究采用Open3D-QSAR进行分析，因为它使用简单且能够产生值得信赖的结果。在此平台上使用了四个工具进行分析：Py-MolEdit，Py-ConfSearch,和Py-CoMFA。
■生成的图用于确定屏幕的r2(多重测定系数)值和q2(相关系数)。这些数字必须小于1，表明良好的，值得信赖的模型。交叉验证(q2)0.532和常规(r2)0.969的相关值使得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％）。这个假设指出，空间(43.1%)，静电（26.4%），疏水性（20.3％）质量在硬化素抑制剂的设计中很重要。
■使用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。测试集证明了模型的鲁棒性。这项研究可能有助于开发使用FDA批准的药物合成的更有效的硬化素抑制剂。
■在这项研究中，使用3D-QSAR比较分子场分析(CoMFA)研究配体-受体相互作用。CoMFA中的空间和静电特性的估计是使用Lennard-Jones和库仑电位进行的。
■为了确定这些分子活性所必需的条件，选择了50种食品和药物管理局（FDA）批准的药物进行3D-QSAR研究，并由CoMFA完成。对于QSAR分析，有许多可用的工具。这项研究采用Open3D-QSAR进行分析，因为它使用简单且能够产生值得信赖的结果。在此平台上使用了四个工具进行分析：Py-MolEdit，Py-ConfSearch,和Py-CoMFA。
■生成的图用于确定屏幕的r2(多重测定系数)值和q2(相关系数)。这些数字必须小于1，表明良好的，值得信赖的模型。交叉验证(q2)0.532和常规(r2)0.969的相关值使得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％）。这个假设指出，空间(43.1%)，静电（26.4%），疏水性（20.3％）质量在硬化素抑制剂的设计中很重要。
■使用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。测试集证明了模型的鲁棒性。这项研究可能有助于开发使用FDA批准的药物合成的更有效的硬化素抑制剂。
