Integrative Structural Biology in the Era of Accurate Structure Prediction

JOURNAL OF MOLECULAR BIOLOGY

卷:433

Review

Masrati, Gal¹  Landau, Meytal^2,3  Ben-Tal, Nir¹  Lupas, Andrei⁴  Kosloff, Mickey⁵  Kosinski, Jan^3,6,7 

[1] Tel Aviv Univ, George S Wise Fac Life Sci, Dept Biochem & Mol Biol, IL-6997801 Tel Aviv, Israel

[2] Technion Israel Inst Technol, Dept Biol, IL-3200003 Haifa, Israel

[3] European Mol Biol Lab EMBL, D-22607 Hamburg, Germany

[4] Max Planck Inst Dev Biol, Dept Prot Evolut, D-72076 Tubingen, Germany

[5] Univ Haifa, Fac Nat Sci, Dept Human Biol, 199 Aba Khoushy Ave, IL-3498838 Haifa, Israel

[6] Ctr Struct Syst Biol CSSB, D-22607 Hamburg, Germany

[7] European Mol Biol Lab, Struct & Computat Biol Unit, Meyerhofstr 1, D-69117 Heidelberg, Germany

关键词: AlphaFold2;    protein structure prediction;    protein conformations;    X-ray crystallography;    NMR;    cryo-electron microscopy;   

DOI  :  10.1016/j.jmb.2021.167127

来源: Elsevier

【 摘 要 】

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships. (C) 2021 The Authors. Published by Elsevier Ltd.

【 授权许可】

Free