Lisa Lombardo, Salvatore Mirabile, Rosaria Gitto, Giuseppe Cosentino, Stefano Alcaro, Maria Dichiara, Agostino Marrazzo, Emanuele Amata, Francesco Ortuso, Laura De Luca
{"title":"Exploring Structural Requirements for Sigma-1 Receptor Linear Ligands: Experimental and Computational Approaches","authors":"Lisa Lombardo, Salvatore Mirabile, Rosaria Gitto, Giuseppe Cosentino, Stefano Alcaro, Maria Dichiara, Agostino Marrazzo, Emanuele Amata, Francesco Ortuso, Laura De Luca","doi":"10.1021/acs.jcim.4c00500","DOIUrl":null,"url":null,"abstract":"Sigma-1 receptor (S1R) is involved in a large array of biological functions due to its ability to interact with various proteins and ion channels. Crystal structures of human S1R revealed the trimeric organization for which each protomer comprises the ligand binding pocket. This study applied a multistep computational procedure to develop a pharmacophore model obtained from molecular dynamics simulations of available cocrystal structures of well-known S1R ligands. Apart from the well-established positive ionizable and hydrophobic features, the obtained model included an additional specific hydrophobic feature and different excluded volumes, thus increasing the selectivity of the model as well as a more detailed determination of the distance between two essential features. The obtained pharmacophore model passed the validation test by receiver operating characteristic (ROC) curve analysis of active and inactive S1R ligands. Finally, the pharmacophoric performance was experimentally investigated through the synthesis and binding assay of new 4-phenylpiperazine-based compounds. The most active new ligand 2-(3-methyl-1-piperidyl)-1-(4-phenylpiperazin-1-yl)ethanone (<b>3</b>) showed an S1R affinity close to the reference compound haloperidol (<i>K</i><sub>i</sub> values of 4.8 and 2.6 nM, respectively). The proposed pharmacophore model can represent a useful tool to design and discover new potent S1R ligands.","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jcim.4c00500","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
Sigma-1 receptor (S1R) is involved in a large array of biological functions due to its ability to interact with various proteins and ion channels. Crystal structures of human S1R revealed the trimeric organization for which each protomer comprises the ligand binding pocket. This study applied a multistep computational procedure to develop a pharmacophore model obtained from molecular dynamics simulations of available cocrystal structures of well-known S1R ligands. Apart from the well-established positive ionizable and hydrophobic features, the obtained model included an additional specific hydrophobic feature and different excluded volumes, thus increasing the selectivity of the model as well as a more detailed determination of the distance between two essential features. The obtained pharmacophore model passed the validation test by receiver operating characteristic (ROC) curve analysis of active and inactive S1R ligands. Finally, the pharmacophoric performance was experimentally investigated through the synthesis and binding assay of new 4-phenylpiperazine-based compounds. The most active new ligand 2-(3-methyl-1-piperidyl)-1-(4-phenylpiperazin-1-yl)ethanone (3) showed an S1R affinity close to the reference compound haloperidol (Ki values of 4.8 and 2.6 nM, respectively). The proposed pharmacophore model can represent a useful tool to design and discover new potent S1R ligands.
期刊介绍:
The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery.
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