Predictions of secondary structure and solvent accessibility of the light chain of the clostridial neurotoxins.

Journal of natural toxins Pub Date : 1998-10-01
F J Lebeda, M A Olson
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Abstract

Predictions were made of the secondary, two-dimensional (2-D) structures and side-chain solvent accessibilities of the light (L) chains of the clostridial neurotoxins (botulinum neurotoxin serotypes A-G and tetanus neurotoxin). An artificial neural network was used to make these predictions from a multiple alignment of their primary structures and was the approach used in making successful predictions for the C-fragments of these neurotoxins (Lebeda et al., J. Prot. Chem., 17:311, 1998). We also exploited the fact that the L-chains are Zn-dependent proteases. Although no other metalloproteases were found to be sequentially homologous to these neurotoxin L-chains, a sequence clustering algorithm showed that several bacterially derived Zn-dependent proteases, including thermolysin, were the most similar. A 2-D structure topology map for the type A L-chain was constructed by using thermolysin as a design template. As in thermolysin, the region containing the Zn-binding sequence motif, which is part of the active site in these neurotoxins, was predicted to be minimally solvent accessible. On the other hand, the locations of residues with highly exposed side chains were predicted to occur in non-periodic structure elements. Together, these 2-D structure and solvent accessibility predictions can be used to identify important solvent-exposed regions of the L-chain. These regions may include sites that interact with residues of the neurotoxin heavy chain, sites that bind to vesicle-docking substrates or sites that form antibody epitopes.

梭状神经毒素轻链的二级结构和溶剂可及性预测。
预测了梭状菌神经毒素(肉毒杆菌神经毒素血清型A-G和破伤风神经毒素)轻(L)链的二级、二维(2-D)结构和侧链溶剂可及性。人工神经网络被用于从其初级结构的多重排列中做出这些预测,并且是成功预测这些神经毒素c片段的方法(Lebeda等人,J. Prot。化学。, 17:311, 1998)。我们还利用了l链是依赖锌的蛋白酶这一事实。虽然没有发现其他金属蛋白酶在序列上与这些神经毒素l链同源,但序列聚类算法显示,几种细菌衍生的锌依赖蛋白酶(包括热溶酶)最相似。以热溶素为设计模板,构建了A型l链的二维结构拓扑图。与热溶素一样,含有锌结合序列基序的区域,是这些神经毒素活性位点的一部分,被预测为最低限度的溶剂可及性。另一方面,具有高度暴露侧链的残基的位置预测出现在非周期结构元素中。总之,这些二维结构和溶剂可及性预测可用于识别l链中重要的溶剂暴露区域。这些区域可能包括与神经毒素重链残基相互作用的位点,与囊泡对接底物结合的位点或形成抗体表位的位点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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