Cecilia Oluwamodupe, Olorunfemi Oyewole Babalola, Paul Olamide Ottu, Erinayo Tolulope Aladeteloye, Elizabeth Temilolaoluwa Mogaji, Elijah Olamide Olumodeji, Victor Richard Adekanle, Olusola Olalekan Elekofehinti
{"title":"The inhibitory effects of <i>Centella asiatica</i> compounds on myeloid cell leukemia 1 (MCL-1) in cancer: a computational study.","authors":"Cecilia Oluwamodupe, Olorunfemi Oyewole Babalola, Paul Olamide Ottu, Erinayo Tolulope Aladeteloye, Elizabeth Temilolaoluwa Mogaji, Elijah Olamide Olumodeji, Victor Richard Adekanle, Olusola Olalekan Elekofehinti","doi":"10.1007/s40203-025-00399-1","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>Centella asiatica</i> 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.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"13 2","pages":"111"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12297120/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"In silico pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40203-025-00399-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.