Computational analysis of membrane proteins: the largest class of drug targets

被引:183
作者
Arinaminpathy, Yalini [1 ]
Khurana, Ekta [1 ]
Engelman, Donald M. [1 ]
Gerstein, Mark B. [1 ]
机构
[1] Yale Univ, Dept Mol Biophys & Biochem, New Haven, CT 06520 USA
关键词
MOLECULAR-DYNAMICS SIMULATIONS; KCSA POTASSIUM CHANNEL; SECONDARY STRUCTURE; BROWNIAN DYNAMICS; STRUCTURAL GENOMICS; RAMAN-SPECTROSCOPY; PREDICTION; MODELS; STATE; CONDUCTION;
D O I
10.1016/j.drudis.2009.08.006
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Given the key roles of integral membrane proteins as transporters and channels, it is necessary to understand their structures and, hence, mechanisms and regulation at the molecular level. Membrane proteins represent similar to 30% of all proteins of currently sequenced genomes. Paradoxically, however, only similar to 2% of crystal structures deposited in the protein data bank are of membrane proteins, and very few of these are at high resolution (better than 2 angstrom). The great disparity between our understanding of soluble proteins and our understanding of membrane proteins is because of the practical problems of working with membrane proteins - specifically, difficulties in expression, purification and crystallization. Thus, computational modeling has been utilized extensively to make crucial advances in understanding membrane protein structure and function.
引用
收藏
页码:1130 / 1135
页数:6
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