{"title":"Targeting GPR52 for potential agonists for schizophrenia therapy: A computational drug discovery study","authors":"Selinay Demir, Güzin Tunca Alparslan","doi":"10.1016/j.jmgm.2025.108994","DOIUrl":null,"url":null,"abstract":"<div><div>G Protein-Coupled Receptors (GPCRs) are one of the most attractive therapeutic targets due to their active role in different systems and disease types. The increasing three-dimensional structure information of GPCRs has made them interesting for Structure-Based Drug Design (SBDD) studies. There are various orphan GPCRs whose endogenous molecules have not yet been identified, although their structural information is known. The recent discovery of the three-dimensional structure of GPR52, an orphan GPCR involved in central nervous system diseases, made it stand out as a drug target. In this study, it is aimed to find a lead drug molecule candidate for GPR52 by using structure-based drug design techniques. The study comprises a set of SBDD methods, including preparation of a small molecule library, pharmacophore modeling, molecular docking, consensus scoring, molecular dynamics simulations, calculation of binding free energy, and <em>in silico</em> pharmacokinetic studies for GPR52. It is expected that the molecules obtained as a result of the study may be strong candidates for <em>in vitro</em> and <em>in vivo</em> experiments or could be used as lead drug molecules in new drug discovery and development studies.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"137 ","pages":"Article 108994"},"PeriodicalIF":2.7000,"publicationDate":"2025-02-21","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/S1093326325000543","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
G Protein-Coupled Receptors (GPCRs) are one of the most attractive therapeutic targets due to their active role in different systems and disease types. The increasing three-dimensional structure information of GPCRs has made them interesting for Structure-Based Drug Design (SBDD) studies. There are various orphan GPCRs whose endogenous molecules have not yet been identified, although their structural information is known. The recent discovery of the three-dimensional structure of GPR52, an orphan GPCR involved in central nervous system diseases, made it stand out as a drug target. In this study, it is aimed to find a lead drug molecule candidate for GPR52 by using structure-based drug design techniques. The study comprises a set of SBDD methods, including preparation of a small molecule library, pharmacophore modeling, molecular docking, consensus scoring, molecular dynamics simulations, calculation of binding free energy, and in silico pharmacokinetic studies for GPR52. It is expected that the molecules obtained as a result of the study may be strong candidates for in vitro and in vivo experiments or could be used as lead drug molecules in new drug discovery and development studies.
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.