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定量构效关系建模揭示了糖尿病中 SIRT1 的去乙酰化底物的最小序列要求和氨基酸偏好。

Quantitative structure-activity relationship modeling reveals the minimal sequence requirement and amino acid preference of sirtuin-1's deacetylation substrates in diabetes mellitus.

机构信息

Department of Nephrology, Suzhou Kowloon Hospital, Shanghai Jiao Tong University, School of Medicine, Suzhou 215000, P. R. China.

出版信息

J Bioinform Comput Biol. 2022 Jun;20(3):2250008. doi: 10.1142/S0219720022500081. Epub 2022 Apr 21.

Abstract

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide ([Formula: see text]-dependent deacetylase involved in multiple glucose metabolism pathways and plays an important role in the pathogenesis of diabetes mellitus (DM). The enzyme specifically recognizes its deacetylation substrates' peptide segments containing a central acetyl-lysine residue as well as a number of amino acids flanking the central residue. In this study, we attempted to ascertain the minimal sequence requirement (MSR) around the central acetyl-lysine residue of SIRT1 substrate-recognition sites as well as the amino acid preference (AAP) at different residues of the MSR window through quantitative structure-activity relationship (QSAR) strategy, which would benefit our understanding of SIRT1 substrate specificity at the molecular level and is also helpful to rationally design substrate-mimicking peptidic agents against DM by competitively targeting SIRT1 active site. In this procedure, a large-scale dataset containing 6801 13-mer acetyl-lysine peptides (and their SIRT1-catalyized deacetylation activities) were compiled to train 10 QSAR regression models developed by systematic combination of machine learning methods (PLS and SVM) and five amino acids descriptors (DPPS, T-scale, MolSurf, [Formula: see text]-score, and FASGAI). The two best QSAR models (PLS+FASGAI and SVM+DPPS) were then employed to statistically examine the contribution of residue positions to the deacetylation activity of acetyl-lysine peptide substrates, revealing that the MSR can be represented by 5-mer acetyl-lysine peptides that meet a consensus motif [Formula: see text][Formula: see text]Formula: see text[Formula: see text]. Structural analysis found that the [Formula: see text] and (AcK) residues are tightly packed against the enzyme active site and confer both stability and specificity for the enzyme-substrate complex, whereas the [Formula: see text], [Formula: see text] and [Formula: see text] residues are partially exposed to solvent but can also effectively stabilize the complex system. Subsequently, a systematic deacetylation activity change profile (SDACP) was created based on QSAR modeling, from which the AAP for each residue position of MSR was depicted. With the profile, we were able to rationally design an SDACP combinatorial library with promising deacetylation activity, from which nine MSR acetyl-lysine peptides as well as two known SIRT1 acetyl-lysine peptide substrates were tested by using SIRT1 deacetylation assay. It is revealed that the designed peptides exhibit a comparable or even higher activity than the controls, although the former is considerably shorter than the latter.

摘要

Sirtuin 1(SIRT1)是一种烟酰胺腺嘌呤二核苷酸([Formula: see text]-依赖性去乙酰化酶,参与多种葡萄糖代谢途径,在糖尿病(DM)发病机制中发挥重要作用。该酶特异性识别其去乙酰化底物的肽段,其中包含中央乙酰-赖氨酸残基以及中央残基周围的一些氨基酸。在这项研究中,我们试图通过定量构效关系(QSAR)策略确定 SIRT1 底物识别位点中中央乙酰-赖氨酸残基周围的最小序列要求(MSR)以及 MSR 窗口中不同残基的氨基酸偏好(AAP),这将有助于我们在分子水平上了解 SIRT1 底物特异性,并且通过竞争性靶向 SIRT1 活性位点,设计针对 DM 的模拟肽类药物也很有帮助。在这个过程中,我们编译了一个包含 6801 个 13 -mer 乙酰-赖氨酸肽(及其 SIRT1 催化的去乙酰化活性)的大型数据集,以通过系统地组合机器学习方法(PLS 和 SVM)和五个氨基酸描述符(DPPS、T-scale、MolSurf、[Formula: see text]-score 和 FASGAI)来训练 10 个 QSAR 回归模型。然后,使用两个最佳的 QSAR 模型(PLS+FASGAI 和 SVM+DPPS)对残基位置对乙酰-赖氨酸肽底物去乙酰化活性的贡献进行统计学检验,结果表明 MSR 可以由满足共识基序[Formula: see text][Formula: see text][Formula: see text](AcK)[Formula: see text]的 5-mer 乙酰-赖氨酸肽表示。结构分析发现,[Formula: see text]和(AcK)残基紧密结合在酶活性位点上,为酶-底物复合物提供了稳定性和特异性,而[Formula: see text]、[Formula: see text]和[Formula: see text]残基部分暴露于溶剂中,但也可以有效地稳定复合物系统。随后,根据 QSAR 建模创建了一个系统的去乙酰化活性变化图谱(SDACP),从中描绘了 MSR 中每个残基位置的 AAP。有了这个图谱,我们就能够合理设计具有潜在去乙酰化活性的 SDACP 组合文库,从中测试了九个 MSR 乙酰-赖氨酸肽以及两种已知的 SIRT1 乙酰-赖氨酸肽底物,使用 SIRT1 去乙酰化测定法进行了测试。结果表明,尽管设计的肽比对照肽短得多,但它们的活性相当或甚至更高。

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