目的:计算生物学分析了蛋白质的理论三级结构,并确定了RhD和RhCE之间的“拓扑”差异。我们的目的是使用计算生物学工具确定RhCE和RhD的四种同工型之间的理论结构差异。
方法:通过疏水性和静电势分析确定物理化学特征。使用计算生物学工具生成二级和三级结构。使用Ramachandran算法对结构进行了评估和验证,计算单个分数,p值和均方根偏差(RMSD)。将结构覆盖在\'RhAG-RhCE-ANK\'(PBDID7uzq)和RhAG的局部细化上,以比较它们在膜内的空间分布。
结果:由于疏水性和静电势的变化,所有蛋白质的表面积和静电距离均不同。RhD和RhCE之间的RMSD为0.46±0.04,RhCE内部的比较为0.57±0.08µ。对于RhD,疏水厚度中氨基酸的百分比为50.24%,而对于RhCE,其范围在73.08%至76.68%之间。RHAG疏水厚度为34.2µ,RhCE的疏水厚度为33.83。我们建议C/c抗原在L1和L2环的表面不同。对于E/e抗原,区别在于L6。相比之下,除Rhce外,所有蛋白质的L4均相同。
结论:Rh蛋白的理化性质使它们不同,尽管它们的基因是同源的。利用计算生物学,我们以足够的精度对结构进行建模,与实验获得的相似。氨基酸变异改变了三级结构的折叠和与其他蛋白质的相互作用,改变静电环境,空间构象和因此的抗原识别。
OBJECTIVE: Computational biology analyses the theoretical tertiary structure of proteins and identifies the \'topological\' differences between RhD and
RhCE. Our aim was to identify the theoretical structural differences between the four isoforms of
RhCE and RhD using computational biological tools.
METHODS: Physicochemical profile was determined by hydrophobicity and electrostatic potential analysis. Secondary and tertiary structures were generated using computational biology tools. The structures were evaluated and validated using Ramachandran algorithm, which calculates the single score, p-value and root mean square deviation (RMSD). Structures were overlaid on local refinement of \'RhAG-RhCE-ANK\' (PBDID 7uzq) and RhAG to compare their spatial distribution within the membrane.
RESULTS: All proteins differed in surface area and electrostatic distance due to variations in hydrophobicity and electrostatic potential. The RMSD between RhD and
RhCE was 0.46 ± 0.04 Å, and the comparison within
RhCE was 0.57 ± 0.08 Å. The percentage of amino acids in the hydrophobic thickness was 50.24% for RhD while for RhCE it ranged between 73.08% and 76.68%. The RHAG hydrophobic thickness was 34.2 Å, and
RhCE\'s hydrophobic thickness was 33.83 Å. We suggest that the C/c antigens differ exofacially at loops L1 and L2. For the E/e antigens, the difference lies in L6. By contrast, L4 is the same for all proteins except
Rhce.
CONCLUSIONS: The physicochemical properties of Rh proteins made them different, although their genes are homologous. Using computational biology, we model structures with sufficient precision, similar to those obtained experimentally. An amino acid variation alters the folding of the tertiary structure and the interactions with other proteins, modifying the electrostatic environment, the spatial conformations and therefore the antigenic recognition.