{"title":"靶点验证和基于结构的虚拟筛选,以发现针对致癌NSD1组蛋白甲基转移酶的潜在先导分子。","authors":"Zahid Rafiq Bhat, Anuj Gahlawat, Navneet Kumar, Nisha Sharma, Prabha Garg, Kulbhushan Tikoo","doi":"10.1007/s40203-023-00158-0","DOIUrl":null,"url":null,"abstract":"<p><p>The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and influence on overall survival in various malignancies. Furthermore, the mRNA and protein expression profile of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the field of cancer therapeutics.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-023-00158-0.</p>","PeriodicalId":13380,"journal":{"name":"In Silico Pharmacology","volume":"11 1","pages":"21"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10421842/pdf/","citationCount":"0","resultStr":"{\"title\":\"Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase.\",\"authors\":\"Zahid Rafiq Bhat, Anuj Gahlawat, Navneet Kumar, Nisha Sharma, Prabha Garg, Kulbhushan Tikoo\",\"doi\":\"10.1007/s40203-023-00158-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. 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引用次数: 0
摘要
该研究的目的是验证核受体结合SET结构域NSD1作为癌症药物靶点,然后设计针对NSD1的先导分子。TCGA临床数据、分子表达技术用于验证靶点,并进行基于结构的虚拟筛选以设计针对NSD1的命中率。临床数据分析表明NSD1在各种恶性肿瘤的转移、预后和对总生存率的影响中的作用。此外,在各种细胞系中评估NSD1的mRNA和蛋白质表达谱。通过基于结构的虚拟筛选方法,使用包括ZINC15和ChemDiv在内的两个主要数据库,NSD1被用作抑制剂的计算机设计的靶蛋白。使用以蛋白质复合物S-腺苷-l-甲硫氨酸(SAM)为内源性配体设计的药效团假说进行虚拟筛选。随后,使用组合得分将前10个化合物与在所有四个得分(对接得分、XP、Gscore、PhaseScreenScore和MMGBSA delta G Bind)中具有高性能的对接筛选化合物区分开来。最后,对前三种锌化合物进行了分子动力学模拟。结合MMGBSA数据表明,ZINC000257261703和ZINC000012405780可用于体外和体内研究,因为它们对NSD1的辅因子结合位点的MMGBSA能量比辛菌素低。我们的数据验证了NSD1是癌症药物靶点,并提供了有前景的结构,可用于进一步的先导优化和合理的药物设计,以打开癌症治疗领域的新大门。图形摘要:补充信息:在线版本包含补充材料,可访问10.1007/s40203-023-00158-0。
Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase.
The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and influence on overall survival in various malignancies. Furthermore, the mRNA and protein expression profile of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the field of cancer therapeutics.
Graphical abstract:
Supplementary information: The online version contains supplementary material available at 10.1007/s40203-023-00158-0.