Cosic I, Hodder A N, Aguilar M I, Hearn M T
Department of Biochemistry, Monash University, Clayton, Victoria, Australia.
Eur J Biochem. 1991 May 23;198(1):113-9. doi: 10.1111/j.1432-1033.1991.tb15993.x.
This study describes the further extension of the resonant recognition model for the analysis and prediction of protein--protein and protein--DNA structure/function dependencies. The model is based on the significant correlation between spectra of numerical presentations of the amino acid or nucleotide sequences of proteins and their coded biological activity. According to this physico-mathematical method, it is possible to define amino acids in the sequence which are predicted to be the most critical for protein function. Using sperm whale myoglobin, human hemoglobin and hen egg white lysozyme as model protein examples, sets of predicted amino acids, or so-called 'hot spots', have been identified within the tertiary structure. It was found for each protein that the predicted 'hot spots', which are distributed along the primary sequence, are spatially grouped in a dome-like arrangement over the active site. The identified amino acids did not correspond to the amino acid residues which are involved in the chemical reaction site of these proteins. It is thus proposed that the resonant recognition model helps to identify amino acid residues which are important for the creation of the molecular structure around the catalytic active site and also the associated physical field conditions required for biorecognition, docking of the specific substrate and full biological activity.
本研究描述了共振识别模型在蛋白质 - 蛋白质及蛋白质 - DNA结构/功能依赖性分析和预测方面的进一步拓展。该模型基于蛋白质氨基酸或核苷酸序列的数值表示谱与其编码的生物活性之间的显著相关性。根据这种物理数学方法，可以确定序列中对蛋白质功能预计最为关键的氨基酸。以抹香鲸肌红蛋白、人血红蛋白和鸡蛋清溶菌酶作为模型蛋白实例，在三级结构内已识别出了几组预测的氨基酸，即所谓的“热点”。对于每种蛋白质，发现沿一级序列分布的预测“热点”在活性位点上方呈穹顶状空间聚集。所识别出的氨基酸并不对应于这些蛋白质化学反应位点所涉及的氨基酸残基。因此有人提出，共振识别模型有助于识别对于在催化活性位点周围创建分子结构以及生物识别、特定底物对接和充分生物活性所需的相关物理场条件而言重要的氨基酸残基。
