跨膜蛋白可溶性变异体的计算设计:一种信息理论方法

Q2 Medicine
Jishnu Das
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引用次数: 0

摘要

该研究检查并实施了一种策略,以建立各种疏水跨膜蛋白的可溶性类似物。这种设计是用一种信息论的方法来完成的,这种方法允许人们在保持其他特性不变的同时干扰蛋白质的某些特性。利用基于知识的力场来获取自身能量和相互作用能量。一种新的后处理技术被添加到理论中,以获得具有控制但不同程度溶解度的类似物库。并非所有由信息理论方法提出的突变都被保留下来。只有由阈值确定的重要突变才会发生。该技术还应用滑动窗口协议,并在某些结构和功能上“非保守”的位置实现点突变。文库方法在突变体的实际实验合成中提供了更大的灵活性。即使在改变的环境中,总体结构和功能特性也得以保留,这一点通过比对和同源建模得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational design of soluble variants of transmembrane proteins: an information theoretic approach
The study examines and implements a strategy to build soluble analogues of various hydrophobic transmembane proteins. The design is done using an information-theoretic approach which allows one to perturb certain properties of the protein while keeping the others constant. Knowledge-based force fields are used to obtain self and cross-interaction energies. A novel postprocessing technique is added to the theory to obtain a library of analogues with controlled but varying degrees of solubility. Not all mutations suggested by the information theoretic approach are kept. Only the significant mutations as determined by a threshold value are made. The technique also applies a sliding window protocol and implements point mutations at certain structurally and functionally 'non-conserved' locations. The library approach provides greater flexibility during actual experimental synthesis of the mutant. The overall structural and functional properties are preserved even in the altered context and this is validated by alignment and homology modelling.
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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