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计算设计 ochratoxin A 的肽配体。

Computational design of peptide ligands for ochratoxin A.

机构信息

Cranfield Health, Cranfield University, Cranfield, Bedfordshire MK43 0AL, England, UK.

出版信息

Toxins (Basel). 2013 Jun 21;5(6):1202-18. doi: 10.3390/toxins5061202.

DOI:10.3390/toxins5061202
PMID:23793075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3717777/
Abstract

In this paper, we describe a peptide library designed by computational modelling and the selection of two peptide sequences showing affinity towards the mycotoxin, ochratoxin A (OTA). A virtual library of 20 natural amino acids was used as building blocks to design a short peptide library against ochratoxin A template using the de novo design program, LeapFrog, and the dynamic modelling software, FlexiDock. Peptide sequences were ranked according to calculated binding scores in their capacity to bind to ochratoxin A. Two high scoring peptides with the sequences N'-Cys-Ser-Ile-Val-Glu-Asp-Gly-Lys-C' (octapeptide) and N'-Gly-Pro-Ala-Gly-Ile-Asp-Gly-Pro-Ala-Gly-Ile-Arg-Cys-C' (13-mer) were selected for synthesis from the resulting database. These synthesized peptides were characterized using a microtitre plate-based binding assay and a surface plasmon resonance biosensor (Biacore 3000). The binding assay confirmed that both de novo designed peptides did bind to ochratoxin A in vitro. SPR analysis confirmed that the peptides bind to ochratoxin A, with calculated K(D) values of ~15.7 μM (13-mer) and ~11.8 μM (octamer). The affinity of the peptides corresponds well with the molecular modelling results, as the 13-mer peptide affinity is about 1.3-times weaker than the octapeptide; this is in accordance with the binding energy values modelled by FlexiDock. This work illustrates the potential of using computational modelling to design a peptide sequence that exhibits in vitro binding affinity for a small molecular weight toxin.

摘要

在本文中,我们描述了一个通过计算建模设计的肽文库,并选择了两个对真菌毒素赭曲霉毒素 A (OTA)具有亲和力的肽序列。使用 20 种天然氨基酸的虚拟文库作为构建块,使用从头设计程序 LeapFrog 和动态建模软件 FlexiDock 针对 OTA 模板设计短肽文库。肽序列根据其结合 OTA 的能力计算结合评分进行排序。根据计算的结合评分,选择两个得分较高的肽序列 N'-Cys-Ser-Ile-Val-Glu-Asp-Gly-Lys-C'(八肽)和 N'-Gly-Pro-Ala-Gly-Ile-Asp-Gly-Pro-Ala-Gly-Ile-Arg-Cys-C'(十三肽)用于从结果数据库中合成。从合成的肽中,使用微量滴定板结合测定和表面等离子体共振生物传感器(Biacore 3000)进行了表征。结合测定证实,这两种从头设计的肽都可以在体外与 OTA 结合。SPR 分析证实了这些肽与 OTA 的结合,计算出的 K(D)值分别约为 15.7 μM(十三肽)和 11.8 μM(八肽)。肽的亲和力与分子建模结果非常吻合,因为十三肽的亲和力比八肽弱约 1.3 倍;这与 FlexiDock 模拟的结合能值一致。这项工作说明了使用计算建模设计表现出对小分子毒素体外结合亲和力的肽序列的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/c961f59546e5/toxins-05-01202-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/e9e16e2220c3/toxins-05-01202-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/e66191ce086f/toxins-05-01202-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/9be60caac43a/toxins-05-01202-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/baaf6421b0aa/toxins-05-01202-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/c961f59546e5/toxins-05-01202-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/e9e16e2220c3/toxins-05-01202-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/e66191ce086f/toxins-05-01202-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/9be60caac43a/toxins-05-01202-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/baaf6421b0aa/toxins-05-01202-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfcf/3717777/c961f59546e5/toxins-05-01202-g005.jpg

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