Computational stabilization of human growth hormone
Computational stabilization of human growth hormone
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DOI：
10.1110/ps.3500102
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发表时间：
2002-06-01
期刊：
影响因子：
8
通讯作者：
Dahiyat, BI
中科院分区：
文献类型：
--
作者：
Filikov, AV;Hayes, RJ;Dahiyat, BI
重组人生长激素(HGH)在全世界范围内被用于治疗儿童甲状腺功能减退侏儒症和患有低水平hGH的儿童。它在溶液中的稳定性有限，而且由于口服吸收不良，通常一周注射几次。因此，开发的重点是更稳定或更缓释的制剂和可注射递送的替代品，这些制剂将提高生物利用度，并使患者更容易使用。我们通过计算赎回了hGH，以提高其热稳定性。更稳定的hGH变种可以改善药代动力学或延长货架期，或者更易于在替代给药系统和配方中使用。计算设计是使用先前开发的基于死端消除定理的组合优化算法进行的。该算法使用经验自由能函数对设计的序列进行评分。这个函数增加了一个术语，解释了主链和侧链构象熵的损失。通过最小化算法设计的相对于野生型的突变数量，优化了该项、静电相互作用项和极性氢埋项的权重因子。用改进的势函数对蛋白质核心区的45个残基进行优化。使用开发的评分功能设计的蛋白质包含6到10个突变，在高达16摄氏度的融化温度中表现出增强，并在细胞增殖研究中具有生物活性。这些结果显示了我们的自由能函数在蛋白质自动设计中的应用。
Recombinant human growth hormone (hGH) is used worldwide for the treatment of pediatric hypopituitary dwarfism and in children suffering from low levels of hGH. It has limited stability in solution, and because of poor oral absorption, is administered by injection, typically several times a week. Development has therefore focused on more stable or sustained-release formulations and alternatives to injectable delivery that would increase bioavailability and make it easier for patients to use. We redesioned hGH computationally to improve its thermostability. A more stable variant of hGH could have improved pharmacokinetics or enhanced shelf-life, or be more amenable to use in alternate delivery systems and formulations. The computational design was performed using a previously developed combinatorial optimization algorithm based on the dead-end elimination theorem. The al-orithm uses an empirical free energy function for scoring designed sequences. This function was augmented with a term that accounts for the loss of backbone and side-chain conformational entropy. The weighting factors for this term, the electrostatic interaction term, and the polar hydrogen burial term were optimized by minimizing the number of mutations designed by the algorithm relative to wild-type. Forty-five residues in the core of the protein were selected for optimization with the modified potential function. The proteins designed using the developed scoring function contained six to 10 mutations, showed enhancement in the melting temperature of up to 16degreesC, and were biologically active in cell proliferation studies. These results show the utility of our free energy function in automated protein design.