Computational modeling of protein assemblies

被引:29
|
作者
Soni, Neelesh [1 ]
Madhusudhan, M. S. [1 ,2 ]
机构
[1] Indian Inst Sci Educ & Res, Pune Dr Homi Bhabha Rd, Pune 411008, Maharashtra, India
[2] ASTAR, Bioinformat Inst, 30 Biopolis St,#07-01 Matrix, Singapore 138671, Singapore
基金
英国惠康基金;
关键词
MOLECULAR-SURFACE RECOGNITION; MACROMOLECULAR ASSEMBLIES; CROSS-LINKING; STRUCTURAL-CHARACTERIZATION; CRYOELECTRON MICROSCOPY; SHAPE COMPLEMENTARITY; CONFORMATIONAL STATES; INTERACTION NETWORKS; ELECTRON-MICROSCOPY; WEB SERVER;
D O I
10.1016/j.sbi.2017.04.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Computational methods to predict the 3D structures of protein interactions fall into 3 categories-template based modeling, protein-protein docking and hybrid/integrative modeling. The two most important considerations for modeling methods are sampling and scoring conformations. Sampling has benefitted from techniques such as fast Fourier transforms (FFT), spherical harmonics and higher order manifolds. Scoring complexes to determine binding free energy is still a challenging problem. Rapid advances have been made in hybrid modeling where experimental data are amalgamated with computations. These methods have received a boost from the popularity of experimental methods such as electron microscopy (EM). While increasingly larger and complicated complexes are now getting elucidated by integrative methods, modeling conformational flexibility remains a challenge. Ongoing improvements to these techniques portend a future where organelles or even cells could be accurately modeled at a molecular level.
引用
收藏
页码:179 / 189
页数:11
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