AI-Driven Deep Learning Techniques in Protein Structure Prediction

Kennesaw State University · Bowling Green State University · +2 more institutions

PubMed
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Abstract

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This…

Citation impact

112
total citations
FWCI
23.29
Percentile
100%
References
131
Citations per year

Authors

10

Topics & keywords

Keywords
  • CASP
  • Protein structure prediction
  • Threading (protein sequence)
  • Artificial intelligence
  • Computer science
  • Protein structure
  • Homology modeling
  • Machine learning
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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Funding