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Signal Transduction and Targeted Therapy, volume 8, issue 1, publication number 115

AlphaFold2 and its applications in the fields of biology and medicine

ZHENYU YANG 1
Xiaoxi Zeng 1
Yi Zhao 1, 2
RUNSHENG CHEN 1, 3, 4
2
 
Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
3
 
Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
4
 
Pingshan translational medicine center, Shenzhen Bay Laboratory, Shenzhen, China
Publication typeJournal Article
Publication date2023-03-14
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor39.3
ISSN20959907, 20593635
Cancer Research
Genetics
Abstract

AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

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GOST Copy
YANG Z. et al. AlphaFold2 and its applications in the fields of biology and medicine // Signal Transduction and Targeted Therapy. 2023. Vol. 8. No. 1. 115
GOST all authors (up to 50) Copy
YANG Z., Zeng X., Zhao Y., CHEN R. AlphaFold2 and its applications in the fields of biology and medicine // Signal Transduction and Targeted Therapy. 2023. Vol. 8. No. 1. 115
RIS |
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RIS Copy
TY - JOUR
DO - 10.1038/s41392-023-01381-z
UR - https://doi.org/10.1038/s41392-023-01381-z
TI - AlphaFold2 and its applications in the fields of biology and medicine
T2 - Signal Transduction and Targeted Therapy
AU - YANG, ZHENYU
AU - Zeng, Xiaoxi
AU - Zhao, Yi
AU - CHEN, RUNSHENG
PY - 2023
DA - 2023/03/14 00:00:00
PB - Springer Nature
IS - 1
VL - 8
SN - 2095-9907
SN - 2059-3635
ER -
BibTex
Cite this
BibTex Copy
@article{2023_YANG,
author = {ZHENYU YANG and Xiaoxi Zeng and Yi Zhao and RUNSHENG CHEN},
title = {AlphaFold2 and its applications in the fields of biology and medicine},
journal = {Signal Transduction and Targeted Therapy},
year = {2023},
volume = {8},
publisher = {Springer Nature},
month = {mar},
url = {https://doi.org/10.1038/s41392-023-01381-z},
number = {1},
doi = {10.1038/s41392-023-01381-z}
}
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