{"title":"A novel in silico approach for identifying multi-target JAK/STAT inhibitors as anticancer agents","authors":"Alessia Bono , Gabriele La Monica , Federica Alamia , Antonino Lauria , Annamaria Martorana","doi":"10.1016/j.jmgm.2024.108913","DOIUrl":null,"url":null,"abstract":"<div><div>Apoptosis, or programmed cell death, plays a pivotal role in maintaining cellular homeostasis by eliminating damaged or surplus cells. Dysregulation of signaling pathways, such as JAK/STAT, is implicated in various diseases, rendering them attractive therapeutic targets for potential new anticancer drugs. Concurrently, it is imperative to preserve essential proteins like TNF-α and p53 to maintain normal cellular life/death balance. In light of these considerations, this study employs an innovative <em>in silico</em> hybrid and hierarchical virtual screening approach aimed at identifying JAK/STAT multi-target inhibitors as potential anticancer agents for several tumoral diseases. Initially, the Biotarget Predictor Tool is utilized in a combined ON/OFF-target/Multitarget mode using the extensive National Cancer Institute (NCI) database, previously filtered by ADME evaluation tools. Subsequently, Molecular Docking studies are conducted on JAK2, JAK3, and STAT3, facilitating the identification of the most promising compound, <strong>755435</strong>. Finally, Molecular Dynamics Simulations validate the high stability of the potential multitarget inhibitor <strong>755435</strong> in complex with JAK2, JAK3, and STAT3.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"135 ","pages":"Article 108913"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of molecular graphics & modelling","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1093326324002134","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Apoptosis, or programmed cell death, plays a pivotal role in maintaining cellular homeostasis by eliminating damaged or surplus cells. Dysregulation of signaling pathways, such as JAK/STAT, is implicated in various diseases, rendering them attractive therapeutic targets for potential new anticancer drugs. Concurrently, it is imperative to preserve essential proteins like TNF-α and p53 to maintain normal cellular life/death balance. In light of these considerations, this study employs an innovative in silico hybrid and hierarchical virtual screening approach aimed at identifying JAK/STAT multi-target inhibitors as potential anticancer agents for several tumoral diseases. Initially, the Biotarget Predictor Tool is utilized in a combined ON/OFF-target/Multitarget mode using the extensive National Cancer Institute (NCI) database, previously filtered by ADME evaluation tools. Subsequently, Molecular Docking studies are conducted on JAK2, JAK3, and STAT3, facilitating the identification of the most promising compound, 755435. Finally, Molecular Dynamics Simulations validate the high stability of the potential multitarget inhibitor 755435 in complex with JAK2, JAK3, and STAT3.
期刊介绍:
The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.
As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.