Recent Progress for Structure and Function Prediction of Protein and RNA, 2nd Edition
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: closed (31 March 2025) | Viewed by 188
Special Issue Editors
Interests: protein structure prediction; protein function prediction; RNA/DNA structure prediction; deep learning; structure bioinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: protein structure prediction and analysis; machine learning application in bioinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: structural bioinformatics; statistical genomics; transcriptomics; intrinsically disordered proteins; single cell omics
Special Issues, Collections and Topics in MDPI journals
Interests: protein–ligand docking; protein structure modeling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Deep learning techniques have significantly impacted the prediction of protein/RNA structure and function. In particular, after DeepMind released their end-to-end deep learning protein structure prediction tool, AlphaFold2, the computational biology field changed greatly. The use of AlphaFold2 and multiple sequence alignment generation, co-evolutionary-based contact/distance prediction, template detection, domain partition and assembly, deep learning-based spatial restraint prediction, protein folding by L-BFGS or Monte Carlo simulation, most cutting-edge attention and transformer mechanisms in deep learning, and so on. These topics are the foundation for the success of protein structure prediction. Furthermore, deep learning has also shown a powerful impact on protein function prediction and RNA-related research. The main focus of this Special Issue is the description of novel computational algorithms, software, models, and tools, including statistical methods, machine learning, deep learning, and artificial intelligence, on data across different areas of computational structure biology, including protein structure prediction, protein function prediction, and corresponding research on RNA/DNA.
Dr. Wei Zheng
Dr. Jianzhao Gao
Dr. Gang Hu
Dr. Yang Cao
Guest Editors
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Keywords
- protein structure prediction
- protein function prediction
- RNA structure prediction
- protein–ligand binding
- end-to-end protein folding
- distance-map prediction
- model quality estimation
- protein–protein complex
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