AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function

被引：152

作者：

Skolnick, Jeffrey ^{[1
]}

Gao, Mu ^{[1
]}

Zhou, Hongyi ^{[1
]}

Singh, Suresh ^{[2
]}

机构：

[1] Georgia Inst Technol, Ctr Study Syst Biol, Sch Biol Sci, Atlanta, GA 30332 USA

[2] Twilight Design, Kendall Pk, NJ 08824 USA

来源：

JOURNAL OF CHEMICAL INFORMATION AND MODELING | 2021年 / 61卷 / 10期

关键词：

STRUCTURE PREDICTION; CORRELATED MUTATIONS; LIKELY COMPLETENESS; GLOBULAR-PROTEINS; I-TASSER; POTENTIALS; RESTRAINTS; DATABASE; PACKING;

D O I：

10.1021/acs.jcim.1c01114

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

AlphaFold 2 (AF2) was the star of CASP14, the last biannual structure prediction experiment. Using novel deep learning, AF2 predicted the structures of many difficult protein targets at or near experimental resolution. Here, we present our perspective of why AF2 works and show that it is a very sophisticated fold recognition algorithm that exploits the completeness of the library of single domain PDB structures. It has also learned local side chain packing rearrangements that enable it to refine proteins to high resolution. The benefits and limitations of its ability to predict the structures of many more proteins at or close to atomic detail are discussed.

引用

页码：4827 / 4831

页数：5

共 65 条

[1] Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14 [J].

Anishchenko, Ivan ;

Baek, Minkyung ;

Park, Hahnbeom ;

Hiranuma, Naozumi ;

Kim, David E. ;

Dauparas, Justas ;

Mansoor, Sanaa ;

Humphreys, Ian R. ;

Baker, David .

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2021, 89 (12) :1722-1733

[2]

[Anonymous], ALPHA FOLD PROTEIN S

[3]

[Anonymous], 14th community wide experiment on the critical assessment of techniques for protein structure prediction (CASP14)

[4]

[Anonymous], AF2 IS HER WHATS STR

[5] Accurate prediction of protein structures and interactions using a three-track neural network [J].

Baek, Minkyung ;

DiMaio, Frank ;

Anishchenko, Ivan ;

Dauparas, Justas ;

Ovchinnikov, Sergey ;

Lee, Gyu Rie ;

Wang, Jue ;

Cong, Qian ;

Kinch, Lisa N. ;

Schaeffer, R. Dustin ;

Millan, Claudia ;

Park, Hahnbeom ;

Adams, Carson ;

Glassman, Caleb R. ;

DeGiovanni, Andy ;

Pereira, Jose H. ;

Rodrigues, Andria V. ;

van Dijk, Alberdina A. ;

Ebrecht, Ana C. ;

Opperman, Diederik J. ;

Sagmeister, Theo ;

Buhlheller, Christoph ;

Pavkov-Keller, Tea ;

Rathinaswamy, Manoj K. ;

Dalwadi, Udit ;

Yip, Calvin K. ;

Burke, John E. ;

Garcia, K. Christopher ;

Grishin, Nick V. ;

Adams, Paul D. ;

Read, Randy J. ;

Baker, David .

SCIENCE, 2021, 373 (6557) :871-+

[6] A METHOD TO IDENTIFY PROTEIN SEQUENCES THAT FOLD INTO A KNOWN 3-DIMENSIONAL STRUCTURE [J].

BOWIE, JU ;

LUTHY, R ;

EISENBERG, D .

SCIENCE, 1991, 253 (5016) :164-170

[7] A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation [J].

Brylinski, Michal ;

Skolnick, Jeffrey .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (01) :129-134

[8] Combination of deep neural network with attention mechanism enhances the explainability of protein contact prediction [J].

Chen, Chen ;

Wu, Tianqi ;

Guo, Zhiye ;

Cheng, Jianlin .

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2021, 89 (06) :697-707

[9] Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies [J].

Chen, Jianzhong ;

Wang, Wei ;

Sun, Haibo ;

Pang, Laixue ;

Bao, Huayin .

COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 134

[10]

CHOTHIA C, 1990, ANNU REV BIOCHEM, V59, P1007, DOI 10.1146/annurev.biochem.59.1.1007

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