Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families
Histone deacetylases(HDACs)are an important class of drug targets for the treatment of cancers,neurodegenerative diseases,and other types of diseases.Virtual screening(VS)has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors(HDACIs).To facilitate the process,we constructed maximal unbiased benchmarking data sets for HDACs(MUBD-HDACs)using our recently published methods that were originally developed for building unbiased benchmarking sets for Iigand-based virtual screening(LBVS).The MUBD-HDACs cover all four classes including Class Ⅲ(Sirtuins family)and 14 HDAC isoforms,composed of 631 inhibitors and 24 609 unbiased decoys.Its ligand sets have been validated extensively as chemically diverse,while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of ”artificial enrichment” and ”analogue bias”.We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDACS targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches.In addition,we defined a novel metric,i.e.NLBScore,to detect the ”2D bias” and ”LBVS favorable” effect within the benchmarking sets.In summary,MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs(including Sirtuins)that are available so far.MUBD-HDACs are freely available at http://www.xswlab.org/.
Jie Xia Ermias Lemma Tilahun Eyob Hailu Kebede Terry-Elinor Reid Liangren Zhang Xiang Simon Wang
State Key Laboratory of Natural and Biomimetic Drugs,School of Pharmaceutical Sciences,Peking Univer Molecular Modeling and Drug Discovery Core for District of Columbia Developmental Center for AIDS Re State Key Laboratory of Natural and Biomimetic Drugs,School of Pharmaceutical Sciences,Peking Univer
国内会议
大连
英文
119-133
2016-09-24（万方平台首次上网日期，不代表论文的发表时间）