Indian Institute of Science Education and Research, Pune. Dr. Homi Bhabha Road, Pashan, Pune 411008, India.
Indian Institute of Science Education and Research, Pune. Dr. Homi Bhabha Road, Pashan, Pune 411008, India; Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, 138671, Singapore.
Curr Opin Struct Biol. 2017 Jun;44:179-189. doi: 10.1016/j.sbi.2017.04.006. Epub 2017 May 12.
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.
计算方法预测蛋白质相互作用的 3D 结构分为 3 类——基于模板的建模、蛋白质-蛋白质对接和混合/综合建模。建模方法最重要的两个考虑因素是采样和评分构象。采样受益于快速傅里叶变换 (FFT)、球谐函数和高阶流形等技术。评分复合物以确定结合自由能仍然是一个具有挑战性的问题。在将实验数据与计算相结合的混合建模中取得了快速进展。这些方法受到电子显微镜 (EM) 等实验方法普及的推动。虽然现在越来越多的更大、更复杂的复合物通过整合方法得到阐明,但建模构象灵活性仍然是一个挑战。对这些技术的不断改进预示着未来可以在分子水平上准确地模拟细胞器甚至细胞。