Adaptation of Google DeepMind AI AlphaFold2 in Single Protein 3D Structure Prediction: A Critical Review

AlphaFold2, a deep neural network developed by Google DeepMind, revolutionized structural biology following its groundbreaking performance at the 2020 Critical Assessment of Structure Prediction (CASP) competition, where it achieved unprecedented near-experimental accuracy, significantly outperforming other computational models. This paper critically reviews AlphaFold2’s phased integration into protein science, evaluating its impact on three-dimensional protein structure prediction, its feasibility, and positioning within Gartner's Hype Cycle. Additionally, this review explores how AlphaFold2 accelerated artificial intelligence (AI)-driven protein structure prediction and highlights the potential of deep learning in scientific research. Finally, the future role of AlphaFold2 and its reception within the scientific community are considered.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-02
DOI
https://doi.org/10.5281/zenodo.14955108
Primary Topic
RNA Interference and Gene Delivery
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptation of Google DeepMind AI AlphaFold2 in Single Protein 3D Structure Prediction: A Critical Review

Zenodo (CERN European Organization for Nuclear Research)
RNA Interference and Gene Delivery
article

Adaptation of Google DeepMind AI AlphaFold2 in Single Protein 3D Structure Prediction: A Critical Review

article en

Abstract

AlphaFold2, a deep neural network developed by Google DeepMind, revolutionized structural biology following its groundbreaking performance at the 2020 Critical Assessment of Structure Prediction (CASP) competition, where it achieved unprecedented near-experimental accuracy, significantly outperforming other computational models. This paper critically reviews AlphaFold2’s phased integration into protein science, evaluating its impact on three-dimensional protein structure prediction, its feasibility, and positioning within Gartner's Hype Cycle. Additionally, this review explores how AlphaFold2 accelerated artificial intelligence (AI)-driven protein structure prediction and highlights the potential of deep learning in scientific research. Finally, the future role of AlphaFold2 and its reception within the scientific community are considered.

Zenodo (CERN European Organization for Nuclear Research)
University of Staffordshire (GB)
Openalex Percentile: Top 62%
RNA Interference and Gene Delivery
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.