Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, P.O. Box 71345-1583, Shiraz, Iran.
Appl Biochem Biotechnol. 2024 Sep;196(9):6269-6295. doi: 10.1007/s12010-023-04819-w. Epub 2024 Feb 3.
With the demand for mass production of protein drugs, solubility has become a serious issue. Extrinsic and intrinsic factors both affect this property. A homotetrameric cofactor-free urate oxidase (UOX) is not sufficiently soluble. To engineer UOX for optimum solubility, it is important to identify the most effective factor that influences solubility. The most effective feature to target for protein engineering was determined by measuring various solubility-related factors of UOX. A large library of homologous sequences was obtained from the databases. The data was reduced to six enzymes from different organisms. On the basis of various sequence- and structure-derived elements, the most and the least soluble enzymes were defined. To determine the best protein engineering target for modification, features of the most and least soluble enzymes were compared. Metabacillus fastidiosus UOX was the most soluble enzyme, while Agrobacterium globiformis UOX was the least soluble. According to the comparison-constant method, positive surface patches caused by arginine residue distribution are appropriate targets for modification. Two Arg to Ala mutations were introduced to the least soluble enzyme to test this hypothesis. These mutations significantly enhanced the mutant's solubility. While different algorithms produced conflicting results, it was difficult to determine which proteins were most and least soluble. Solubility prediction requires multiple algorithms based on these controversies. Protein surfaces should be investigated regionally rather than globally, and both sequence and structural data should be considered. Several other biotechnological products could be engineered using the data reduction and comparison-constant methods used in this study.
随着对蛋白质药物大规模生产的需求，溶解度已成为一个严重的问题。外在和内在因素都影响着这一特性。一种四聚体非辅因子游离尿酸氧化酶（UOX）的溶解度不够。为了使 UOX 工程化以达到最佳的溶解度，确定影响溶解度的最有效因素非常重要。通过测量 UOX 的各种与溶解度相关的因素，确定了针对蛋白质工程的最有效特征。从数据库中获得了大量同源序列库。数据减少到来自不同生物体的六种酶。基于各种序列和结构衍生元素，确定了最易溶和最难溶的酶。为了确定最佳的蛋白质工程修饰目标，比较了最易溶和最难溶酶的特征。嗜热脂肪芽孢杆菌 UOX 是最易溶的酶，而球形节杆菌 UOX 是最难溶的酶。根据比较常数法，由精氨酸残基分布引起的正表面斑是修饰的合适目标。将两个 Arg 突变为 Ala 突变引入到最难溶的酶中，以验证这一假设。这些突变显著提高了突变体的溶解度。尽管不同的算法产生了相互矛盾的结果，但很难确定哪些蛋白质最易溶和最难溶。由于存在这些争议，溶解度预测需要基于多种算法。蛋白质表面应进行区域而非全局研究，应同时考虑序列和结构数据。利用本研究中使用的数据减少和比较常数方法，可以对其他几种生物技术产品进行工程化。
