Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
Nat Biotechnol. 2012 Nov;30(11):1072-80. doi: 10.1038/nbt.2419.
Genomic sequences contain rich evolutionary information about functional constraints on macromolecules such as proteins. This information can be efficiently mined to detect evolutionary couplings between residues in proteins and address the long-standing challenge to compute protein three-dimensional structures from amino acid sequences. Substantial progress has recently been made on this problem owing to the explosive growth in available sequences and the application of global statistical methods. In addition to three-dimensional structure, the improved understanding of covariation may help identify functional residues involved in ligand binding, protein-complex formation and conformational changes. We expect computation of covariation patterns to complement experimental structural biology in elucidating the full spectrum of protein structures, their functional interactions and evolutionary dynamics.
基因组序列包含有关蛋白质等大分子的功能限制的丰富进化信息。这些信息可以被有效地挖掘出来，以检测蛋白质中残基之间的进化耦合，并解决长期以来从氨基酸序列计算蛋白质三维结构的挑战。由于可用序列的爆炸式增长和全局统计方法的应用，最近在这个问题上取得了重大进展。除了三维结构，对协变的更好理解可能有助于识别参与配体结合、蛋白质复合物形成和构象变化的功能残基。我们预计协变模式的计算将补充实验结构生物学，以阐明蛋白质结构、它们的功能相互作用和进化动力学的全貌。
