Cecilia Oluwamodupe, Olorunfemi Oyewole Babalola, Paul Olamide Ottu, Erinayo Tolulope Aladeteloye, Elizabeth Temilolaoluwa Mogaji, Elijah Olamide Olumodeji, Victor Richard Adekanle, Olusola Olalekan Elekofehinti
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Molecular docking analyses, including Glide XP (extra precision) were performed to evaluate the binding affinities of the compounds against the prepared crystal structure of MCL-1 (PDB ID: 6FS1) within the Schrödinger Suites. Additionally, the binding free energies of the compounds were computed to assess their thermodynamic stability within the binding pocket. The physicochemical and pharmacokinetic properties of the identified compounds were analyzed based on Lipinski's Rule of Five (RO5), electrostatic potential distribution, and ADME predictions. Predictive models for MCL-1 inhibitors were developed using AutoQSAR to examine the drug-likeness and biological activity of the screened compounds. We found 12 hit compounds, most of which met the RO5 criteria and were in the suggested ADME parameter range. Additionally, the predicted pIC50 values for these compounds were promising, suggesting their potential as MCL-1 inhibitors. 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引用次数: 0
摘要
髓样细胞白血病1 (MCL-1)是b细胞淋巴瘤2 (BCL-2)家族中一个重要的抗凋亡成员,已被广泛证实在多种癌症中过表达,对促进癌细胞存活和治疗耐药性至关重要。MCL-1水平升高已在血液学癌症中被观察到,如急性髓性白血病和多发性骨髓瘤,以及多发性实体瘤。因此,我们使用计算药物发现方法研究了积雪草化合物对MCL-1的潜在抑制作用。通过分子对接分析,包括Glide XP(额外精度)来评估化合物与Schrödinger套件中制备的MCL-1 (PDB ID: 6FS1)晶体结构的结合亲和力。此外,计算了化合物的结合自由能,以评估它们在结合袋内的热力学稳定性。根据Lipinski's Rule of Five (RO5)、静电电位分布和ADME预测分析了鉴定化合物的理化和药代动力学性质。使用AutoQSAR建立MCL-1抑制剂的预测模型,以检查筛选的化合物的药物相似性和生物活性。我们发现了12个命中化合物,其中大部分符合RO5标准,并且在建议的ADME参数范围内。此外,这些化合物的预测pIC50值很有希望,表明它们具有作为MCL-1抑制剂的潜力。本研究结果为合理设计针对MCL-1的新型抗癌药物提供了有意义的分析。
The inhibitory effects of Centella asiatica compounds on myeloid cell leukemia 1 (MCL-1) in cancer: a computational study.
Myeloid cell leukemia 1 (MCL-1), a crucial anti-apoptotic member of the B-cell lymphoma 2 (BCL-2) family, has been extensively documented to be overexpressed in a variety of cancers, where it is essential for fostering cancer cell survival and treatment resistance. Elevated levels of MCL-1 have been observed in hematological cancers, such as acute myeloid leukemia and multiple myeloma, as well as in multiple solid tumors. We therefore examined the potential inhibitory effects of Centella asiatica compounds on MCL-1 using a computational drug discovery approach. Molecular docking analyses, including Glide XP (extra precision) were performed to evaluate the binding affinities of the compounds against the prepared crystal structure of MCL-1 (PDB ID: 6FS1) within the Schrödinger Suites. Additionally, the binding free energies of the compounds were computed to assess their thermodynamic stability within the binding pocket. The physicochemical and pharmacokinetic properties of the identified compounds were analyzed based on Lipinski's Rule of Five (RO5), electrostatic potential distribution, and ADME predictions. Predictive models for MCL-1 inhibitors were developed using AutoQSAR to examine the drug-likeness and biological activity of the screened compounds. We found 12 hit compounds, most of which met the RO5 criteria and were in the suggested ADME parameter range. Additionally, the predicted pIC50 values for these compounds were promising, suggesting their potential as MCL-1 inhibitors. The results of this study offer insightful analysis for the rational design of new anticancer treatments aimed at MCL-1.