AI-Driven Deep Learning Techniques in Protein Structure Prediction
Kennesaw State University · Bowling Green State University · +2 more institutions
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
- FWCI
- 23.29
- Percentile
- 100%
- References
- 131
Authors
10Topics & keywords
- CASP
- Protein structure prediction
- Threading (protein sequence)
- Artificial intelligence
- Computer science
- Protein structure
- Homology modeling
- Machine learning
- Industry, innovation and infrastructure