Abstract：
Pyruvate kinase M2 (PKM2) is preferentially expressed as a low-activity dimer over the active tetramer in proliferating tumor cells, resulting in metabolic reprogramming to achieve high energy requirements and nutrient uptake. This leads to a shift from the normal glycolytic pathway causing tumor cells to proliferate uncontrollably. This study utilizes knowledge-based drug discovery to determine the critical features from experimentally known PKM2 activators and design compounds that would significantly confer a stable structural and functional edge over the known compounds which are still at the preclinical stage.
Conscientious molecular modeling studies were carried out and critical structural features were identified and validated from the knowledge of experimentally known PKM2 activators to confer high-binding affinities. A virtual library of 200 palindromic and non-palindromic activators was designed based on these identified critical features to target a distinct activator binding-site. This binding would favor specific dimer-dimer association and subsequent protein tetramerization. The resultant compounds strongly correlated with identified structural features and binding affinities which further strengthened our findings. The designed activators were then subjected to pharmacokinetic profiling and toxicity prediction, followed by free-binding energy calculations and MD simulations.
All the virtually designed activators comprising the identified critical features were observed to confer high-binding affinities ranging from -9.1 to -15.0 kcal/mol to the receptor protein. The designed activators also demonstrated optimum pharmacokinetic and toxicity profiles.
The best activators selected for MD simulations studies were conclusively observed to stabilize the required tetrameric conformation suggesting that these activators could potentially target PKM2 tetramerization that might restore the normal glycolytic pathway and suppress tumor progression.
Conscientious molecular modeling studies were carried out and critical structural features were identified and validated from the knowledge of experimentally known PKM2 activators to confer high-binding affinities. A virtual library of 200 palindromic and non-palindromic activators was designed based on these identified critical features to target a distinct activator binding-site. This binding would favor specific dimer-dimer association and subsequent protein tetramerization. The resultant compounds strongly correlated with identified structural features and binding affinities which further strengthened our findings. The designed activators were then subjected to pharmacokinetic profiling and toxicity prediction, followed by free-binding energy calculations and MD simulations.
All the virtually designed activators comprising the identified critical features were observed to confer high-binding affinities ranging from -9.1 to -15.0 kcal/mol to the receptor protein. The designed activators also demonstrated optimum pharmacokinetic and toxicity profiles.
The best activators selected for MD simulations studies were conclusively observed to stabilize the required tetrameric conformation suggesting that these activators could potentially target PKM2 tetramerization that might restore the normal glycolytic pathway and suppress tumor progression.
摘要：
丙酮酸激酶M2（PKM2）在增殖的肿瘤细胞中优先表达为低活性二聚体，而不是活性四聚体。导致代谢重编程，以实现高能量需求和营养吸收。这导致正常糖酵解途径的转变，导致肿瘤细胞无法控制地增殖。这项研究利用基于知识的药物发现来确定实验已知的PKM2活化剂的关键特征，并设计出与仍处于临床前阶段的已知化合物相比，将显着赋予稳定的结构和功能优势的化合物。
进行了认真的分子建模研究，并根据实验已知的PKM2激活剂的知识鉴定和验证了关键的结构特征，以赋予高结合亲和力。基于这些确定的关键特征来设计200个回文和非回文激活剂的虚拟文库，以靶向不同的激活剂结合位点。这种结合将有利于特异性二聚体-二聚体缔合和随后的蛋白质四聚化。所得化合物与确定的结构特征和结合亲和力密切相关，这进一步加强了我们的发现。然后对设计的活化剂进行药代动力学分析和毒性预测，其次是自由结合能计算和MD模拟。
观察到包含鉴定的关键特征的所有虚拟设计的活化剂赋予受体蛋白-9.1至-15.0kcal/mol的高结合亲和力。设计的活化剂还表现出最佳的药代动力学和毒性曲线。
最终观察到为MD模拟研究选择的最佳激活剂稳定了所需的四聚体构象，表明这些激活剂可能潜在地靶向PKM2四聚化，这可能恢复正常的糖酵解途径并抑制肿瘤进展。
进行了认真的分子建模研究，并根据实验已知的PKM2激活剂的知识鉴定和验证了关键的结构特征，以赋予高结合亲和力。基于这些确定的关键特征来设计200个回文和非回文激活剂的虚拟文库，以靶向不同的激活剂结合位点。这种结合将有利于特异性二聚体-二聚体缔合和随后的蛋白质四聚化。所得化合物与确定的结构特征和结合亲和力密切相关，这进一步加强了我们的发现。然后对设计的活化剂进行药代动力学分析和毒性预测，其次是自由结合能计算和MD模拟。
观察到包含鉴定的关键特征的所有虚拟设计的活化剂赋予受体蛋白-9.1至-15.0kcal/mol的高结合亲和力。设计的活化剂还表现出最佳的药代动力学和毒性曲线。
最终观察到为MD模拟研究选择的最佳激活剂稳定了所需的四聚体构象，表明这些激活剂可能潜在地靶向PKM2四聚化，这可能恢复正常的糖酵解途径并抑制肿瘤进展。
